./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/fit0x0.extension
Regression (Phase-based) SUPER CLEAN
Init
Set Working Directory
Imports
Input and Output Directories and Files
Check Period and Phase in df2
Check Period and Phase in df3
Prepare for Regression
Fitting and Marginalization
Cleanup
Save Data for Reference
Source Helpers
Model fit01aPh: Null
Fit
fit01aPh: [df0] Agency ~ (1 | Name) + 1
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (1 | Name) + 1
Data: df0
Control: control
REML criterion at convergence: 26631.7
Scaled residuals:
Min 1Q Median 3Q Max
-7.9514 -0.5639 -0.0023 0.5683 7.3986
Random effects:
Groups Name Variance Std.Dev.
Name (Intercept) 0.006209 0.0788
Residual 0.067519 0.2598
Number of obs: 169997, groups: Name, 870
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 4.986e-01 2.807e-03 8.264e+02 177.7 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# R2 for Mixed Models
Conditional R2: 0.084
Marginal R2: 0.000
---------------------------------------------------------------------
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# Intraclass Correlation Coefficient
Adjusted ICC: 0.084
Unadjusted ICC: 0.084
---------------------------------------------------------------------
fit01aPh: [df0] Agency ~ (1 | Name) + 1
# ICC by Group
Group | ICC
-------------
Name | 0.084
---------------------------------------------------------------------
Efects: Random
Model fit02aPh: Time
Fit
fit02aPh: [df0] Agency ~ (Time | Name) + Time
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time
Data: df0
Control: control
REML criterion at convergence: 24941.9
Scaled residuals:
Min 1Q Median 3Q Max
-8.0353 -0.5639 -0.0047 0.5664 7.3362
Random effects:
Groups Name Variance Std.Dev. Corr
Name (Intercept) 0.006283 0.07927
Time 0.004088 0.06394 0.18
Residual 0.066384 0.25765
Number of obs: 169997, groups: Name, 870
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.498029 0.002848 816.443563 174.884 < 2e-16 ***
Time -0.010230 0.002634 709.116999 -3.884 0.000112 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# R2 for Mixed Models
Conditional R2: 0.102
Marginal R2: 0.000
---------------------------------------------------------------------
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# Intraclass Correlation Coefficient
Adjusted ICC: 0.102
Unadjusted ICC: 0.102
---------------------------------------------------------------------
fit02aPh: [df0] Agency ~ (Time | Name) + Time
# ICC by Group
Group | ICC
-------------
Name | 0.085
---------------------------------------------------------------------
Effects: Time
Compute
fit02aPh: [df0] Agency ~ (Time | Name) + Time
=====================================================================
# Average predicted values of Agency
Time | Predicted | 95% CI
------------------------------
-1.00 | 0.51 | 0.50, 0.51
-0.50 | 0.50 | 0.50, 0.51
0.00 | 0.50 | 0.49, 0.50
0.50 | 0.50 | 0.49, 0.50
1.00 | 0.49 | 0.48, 0.50
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
--------------------------------
-7.57e-03 | -0.01, 0.00 | 0.004
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
--------------------------------
-7.57e-03 | -0.01, 0.00 | 0.004
Plot: Basic
Model fit03aPh: Time x Phase
Fit
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time * Phase
Data: df0
Control: control
REML criterion at convergence: 24043.7
Scaled residuals:
Min 1Q Median 3Q Max
-8.1156 -0.5629 -0.0072 0.5649 7.3761
Random effects:
Groups Name Variance Std.Dev. Corr
Name (Intercept) 0.006224 0.07889
Time 0.004129 0.06425 0.18
Residual 0.066017 0.25694
Number of obs: 169997, groups: Name, 870
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.285e-01 3.170e-03 1.284e+03 166.749 <2e-16 ***
Time 4.459e-02 3.657e-03 2.769e+03 12.192 <2e-16 ***
PhaseAE -4.145e-03 4.178e-03 1.691e+05 -0.992 0.3212
PhaseBR -5.689e-01 3.066e-02 1.686e+05 -18.558 <2e-16 ***
PhaseAR -9.121e-03 4.936e-03 1.697e+05 -1.848 0.0646 .
Time:PhaseAE -3.579e-01 2.590e-02 1.688e+05 -13.820 <2e-16 ***
Time:PhaseBR 1.610e+00 9.670e-02 1.686e+05 16.650 <2e-16 ***
Time:PhaseAR -9.963e-02 7.213e-03 1.676e+05 -13.812 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# R2 for Mixed Models
Conditional R2: 0.107
Marginal R2: 0.006
---------------------------------------------------------------------
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# Intraclass Correlation Coefficient
Adjusted ICC: 0.102
Unadjusted ICC: 0.101
---------------------------------------------------------------------
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
# ICC by Group
Group | ICC
-------------
Name | 0.085
---------------------------------------------------------------------
Effects: Time
Compute
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
=====================================================================
# Average predicted values of Agency
Time | Predicted | 95% CI
------------------------------
-1.00 | 0.45 | 0.44, 0.47
-0.50 | 0.48 | 0.47, 0.49
0.00 | 0.50 | 0.50, 0.51
0.50 | 0.53 | 0.52, 0.54
1.00 | 0.56 | 0.54, 0.57
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
---------------------------
0.05 | 0.04, 0.06 | < .001
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
---------------------------
0.05 | 0.04, 0.06 | < .001
Plot: Basic
Effects: Phase
Compute
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
=====================================================================
# Average predicted values of Agency
Phase | Predicted | 95% CI
--------------------------------
BE | 0.53 | 0.52, 0.53
AE | 0.55 | 0.54, 0.56
BR | -0.15 | -0.22, -0.08
AR | 0.53 | 0.51, 0.54
=====================================================================
Phase | Predicted | 95% CI | p
-----------------------------------------
BE | 0.53 | 0.52, 0.53 | < .001
AE | 0.55 | 0.54, 0.56 | < .001
BR | -0.15 | -0.22, -0.08 | < .001
AR | 0.53 | 0.51, 0.54 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
----------------------------------------
BE-AE | -0.02 | -0.03, -0.01 | < .001
BE-BR | 0.68 | 0.61, 0.75 | < .001
BE-AR | 2.34e-03 | -0.01, 0.01 | 0.658
AE-BR | 0.70 | 0.63, 0.77 | < .001
AE-AR | 0.02 | 0.01, 0.04 | 0.003
BR-AR | -0.68 | -0.75, -0.60 | < .001
Plot: Basic
Effects: Time x Phase
Compute
fit03aPh: [df0] Agency ~ (Time | Name) + Time * Phase
=====================================================================
# Average predicted values of Agency
Phase: BE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.48 | 0.47, 0.49
-0.50 | 0.51 | 0.50, 0.51
0.00 | 0.53 | 0.52, 0.54
0.50 | 0.56 | 0.55, 0.56
1.00 | 0.58 | 0.57, 0.59
Phase: AE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.84 | 0.78, 0.89
-0.50 | 0.68 | 0.65, 0.71
0.00 | 0.53 | 0.52, 0.54
0.50 | 0.37 | 0.35, 0.39
1.00 | 0.22 | 0.17, 0.26
Phase: BR
Time | Predicted | 95% CI
--------------------------------
-1.00 | -1.70 | -1.95, -1.45
-0.50 | -0.87 | -1.02, -0.71
0.00 | -0.04 | -0.10, 0.02
0.50 | 0.79 | 0.76, 0.83
1.00 | 1.62 | 1.49, 1.75
Phase: AR
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.57 | 0.55, 0.60
-0.50 | 0.55 | 0.53, 0.56
0.00 | 0.52 | 0.51, 0.53
0.50 | 0.50 | 0.49, 0.50
1.00 | 0.47 | 0.46, 0.48
=====================================================================
# (Average) Linear trend for Time
Phase | Slope | 95% CI | p
-------------------------------------
BE | 0.04 | 0.04, 0.05 | < .001
AE | -0.31 | -0.36, -0.26 | < .001
BR | 1.65 | 1.47, 1.84 | < .001
AR | -0.06 | -0.07, -0.04 | < .001
=====================================================================
# (Average) Linear trend for Time
Phase | Contrast | 95% CI | p
----------------------------------------
BE-AE | 0.36 | 0.31, 0.41 | < .001
BE-BR | -1.61 | -1.80, -1.42 | < .001
BE-AR | 0.10 | 0.09, 0.11 | < .001
AE-BR | -1.97 | -2.16, -1.77 | < .001
AE-AR | -0.26 | -0.31, -0.21 | < .001
BR-AR | 1.71 | 1.52, 1.90 | < .001
Plot: Basic
Plot: Nicer
Model fit04aPh: Time x Phase x Outcome
Fit
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Agency ~ (Time | Name) + Time * Phase * Outcome
Data: df0
Control: control
REML criterion at convergence: 23540
Scaled residuals:
Min 1Q Median 3Q Max
-8.1902 -0.5632 -0.0074 0.5639 7.3864
Random effects:
Groups Name Variance Std.Dev. Corr
Name (Intercept) 0.004798 0.06927
Time 0.003348 0.05786 -0.07
Residual 0.065916 0.25674
Number of obs: 169997, groups: Name, 870
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.151e-01 4.450e-03 1.471e+03 115.767 < 2e-16
Time 5.703e-02 5.597e-03 3.426e+03 10.189 < 2e-16
PhaseAE -4.245e-02 7.688e-03 1.693e+05 -5.521 3.38e-08
PhaseBR -4.966e-01 6.025e-02 1.690e+05 -8.242 < 2e-16
PhaseAR -1.195e-01 1.034e-02 1.662e+05 -11.561 < 2e-16
Outcomewinner 2.383e-02 5.853e-03 1.425e+03 4.072 4.92e-05
Time:PhaseAE -4.906e-01 5.053e-02 1.692e+05 -9.710 < 2e-16
Time:PhaseBR 1.152e+00 1.903e-01 1.689e+05 6.052 1.44e-09
Time:PhaseAR -5.823e-02 1.523e-02 1.543e+05 -3.824 0.000131
Time:Outcomewinner -2.039e-02 7.198e-03 3.276e+03 -2.833 0.004646
PhaseAE:Outcomewinner 5.796e-02 9.165e-03 1.692e+05 6.324 2.56e-10
PhaseBR:Outcomewinner -9.406e-02 6.997e-02 1.689e+05 -1.344 0.178864
PhaseAR:Outcomewinner 1.478e-01 1.178e-02 1.679e+05 12.550 < 2e-16
Time:PhaseAE:Outcomewinner 1.675e-01 5.885e-02 1.692e+05 2.846 0.004424
Time:PhaseBR:Outcomewinner 6.256e-01 2.209e-01 1.688e+05 2.832 0.004623
Time:PhaseAR:Outcomewinner -4.478e-02 1.731e-02 1.602e+05 -2.586 0.009706
(Intercept) ***
Time ***
PhaseAE ***
PhaseBR ***
PhaseAR ***
Outcomewinner ***
Time:PhaseAE ***
Time:PhaseBR ***
Time:PhaseAR ***
Time:Outcomewinner **
PhaseAE:Outcomewinner ***
PhaseBR:Outcomewinner
PhaseAR:Outcomewinner ***
Time:PhaseAE:Outcomewinner **
Time:PhaseBR:Outcomewinner **
Time:PhaseAR:Outcomewinner **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# R2 for Mixed Models
Conditional R2: 0.102
Marginal R2: 0.021
---------------------------------------------------------------------
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# Intraclass Correlation Coefficient
Adjusted ICC: 0.083
Unadjusted ICC: 0.081
---------------------------------------------------------------------
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# ICC by Group
Group | ICC
-------------
Name | 0.067
---------------------------------------------------------------------
Parameters
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
# Fixed Effects
Parameter | Coefficient | SE | 95% CI | t(169977) | p
-----------------------------------------------------------------------------------------------------
(Intercept) | 0.52 | 4.45e-03 | [ 0.51, 0.52] | 115.77 | < .001
Time | 0.06 | 5.60e-03 | [ 0.05, 0.07] | 10.19 | < .001
Phase [AE] | -0.04 | 7.69e-03 | [-0.06, -0.03] | -5.52 | < .001
Phase [BR] | -0.50 | 0.06 | [-0.61, -0.38] | -8.24 | < .001
Phase [AR] | -0.12 | 0.01 | [-0.14, -0.10] | -11.56 | < .001
Outcome [winner] | 0.02 | 5.85e-03 | [ 0.01, 0.04] | 4.07 | < .001
Time × Phase [AE] | -0.49 | 0.05 | [-0.59, -0.39] | -9.71 | < .001
Time × Phase [BR] | 1.15 | 0.19 | [ 0.78, 1.52] | 6.05 | < .001
Time × Phase [AR] | -0.06 | 0.02 | [-0.09, -0.03] | -3.82 | < .001
Time × Outcome [winner] | -0.02 | 7.20e-03 | [-0.03, -0.01] | -2.83 | 0.005
Phase [AE] × Outcome [winner] | 0.06 | 9.17e-03 | [ 0.04, 0.08] | 6.32 | < .001
Phase [BR] × Outcome [winner] | -0.09 | 0.07 | [-0.23, 0.04] | -1.34 | 0.179
Phase [AR] × Outcome [winner] | 0.15 | 0.01 | [ 0.12, 0.17] | 12.55 | < .001
(Time × Phase [AE]) × Outcome [winner] | 0.17 | 0.06 | [ 0.05, 0.28] | 2.85 | 0.004
(Time × Phase [BR]) × Outcome [winner] | 0.63 | 0.22 | [ 0.19, 1.06] | 2.83 | 0.005
(Time × Phase [AR]) × Outcome [winner] | -0.04 | 0.02 | [-0.08, -0.01] | -2.59 | 0.010
# Random Effects
Parameter | Coefficient
----------------------------------------
SD (Intercept: Name) | 0.07
SD (Time: Name) | 0.06
Cor (Intercept~Time: Name) | -0.07
SD (Residual) | 0.26
Summary
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
| Characteristic | Beta | 95% CI1 | p-value |
|---|---|---|---|
| Time | 0.06 | 0.05, 0.07 | <0.001 |
| Phase | |||
| AE - BE | 0.01 | 0.00, 0.03 | 0.10 |
| BR - BE | -0.64 | -0.75, -0.53 | <0.001 |
| BR - AE | -0.66 | -0.77, -0.55 | <0.001 |
| AR - BE | -0.04 | -0.06, -0.02 | <0.001 |
| AR - AE | -0.05 | -0.08, -0.03 | <0.001 |
| AR - BR | 0.60 | 0.49, 0.71 | <0.001 |
| Outcome | |||
| winner - loser | 0.04 | 0.00, 0.08 | 0.069 |
| Time * Phase | |||
| Time * AE | -0.49 | -0.59, -0.39 | <0.001 |
| Time * BR | 1.2 | 0.78, 1.5 | <0.001 |
| Time * AR | -0.06 | -0.09, -0.03 | <0.001 |
| Time * Outcome | |||
| Time * winner | -0.02 | -0.03, -0.01 | 0.005 |
| Phase * Outcome | |||
| AE * winner | 0.06 | 0.04, 0.08 | <0.001 |
| BR * winner | -0.09 | -0.23, 0.04 | 0.2 |
| AR * winner | 0.15 | 0.12, 0.17 | <0.001 |
| Time * Phase * Outcome | |||
| Time * AE * winner | 0.17 | 0.05, 0.28 | 0.004 |
| Time * BR * winner | 0.63 | 0.19, 1.1 | 0.005 |
| Time * AR * winner | -0.04 | -0.08, -0.01 | 0.010 |
| Name.sd__(Intercept) | 0.07 | ||
| Name.cor__(Intercept).Time | -0.07 | ||
| Name.sd__Time | 0.06 | ||
| Residual.sd__Observation | 0.26 | ||
| 1 CI = Confidence Interval | |||
Effects: Time
Compute
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
=====================================================================
# Average predicted values of Agency
Time | Predicted | 95% CI
------------------------------
-1.00 | 0.46 | 0.44, 0.47
-0.50 | 0.48 | 0.47, 0.49
0.00 | 0.50 | 0.50, 0.51
0.50 | 0.53 | 0.52, 0.54
1.00 | 0.55 | 0.54, 0.56
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
---------------------------
0.05 | 0.04, 0.06 | < .001
=====================================================================
# (Average) Linear trend for Time
Slope | 95% CI | p
---------------------------
0.05 | 0.04, 0.06 | < .001
Plot: Basic
Effects: Phase
Compute
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
=====================================================================
# Average predicted values of Agency
Phase | Predicted | 95% CI
--------------------------------
BE | 0.52 | 0.52, 0.53
AE | 0.55 | 0.54, 0.57
BR | -0.12 | -0.19, -0.04
AR | 0.51 | 0.50, 0.52
=====================================================================
Phase | Predicted | 95% CI | p
-----------------------------------------
BE | 0.52 | 0.52, 0.53 | < .001
AE | 0.55 | 0.54, 0.57 | < .001
BR | -0.12 | -0.19, -0.04 | 0.004
AR | 0.51 | 0.50, 0.52 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
----------------------------------------
BE-AE | -0.03 | -0.04, -0.02 | < .001
BE-BR | 0.64 | 0.56, 0.72 | < .001
BE-AR | 0.02 | 0.00, 0.03 | 0.007
AE-BR | 0.67 | 0.59, 0.75 | < .001
AE-AR | 0.05 | 0.03, 0.06 | < .001
BR-AR | -0.62 | -0.70, -0.55 | < .001
Plot: Basic
Effects: Time x Phase
Compute
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
=====================================================================
# Average predicted values of Agency
Phase: BE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.48 | 0.48, 0.49
-0.50 | 0.51 | 0.50, 0.51
0.00 | 0.53 | 0.52, 0.53
0.50 | 0.55 | 0.54, 0.56
1.00 | 0.57 | 0.56, 0.58
Phase: AE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.86 | 0.80, 0.92
-0.50 | 0.69 | 0.66, 0.72
0.00 | 0.53 | 0.52, 0.53
0.50 | 0.36 | 0.34, 0.38
1.00 | 0.19 | 0.15, 0.24
Phase: BR
Time | Predicted | 95% CI
--------------------------------
-1.00 | -1.65 | -1.90, -1.40
-0.50 | -0.84 | -1.00, -0.69
0.00 | -0.03 | -0.09, 0.03
0.50 | 0.78 | 0.74, 0.81
1.00 | 1.59 | 1.46, 1.72
Phase: AR
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.55 | 0.53, 0.58
-0.50 | 0.53 | 0.51, 0.55
0.00 | 0.51 | 0.50, 0.52
0.50 | 0.49 | 0.48, 0.49
1.00 | 0.47 | 0.46, 0.47
=====================================================================
# (Average) Linear trend for Time
Phase | Slope | 95% CI | p
-----------------------------------------
BE | 0.06 | 0.05, 0.07 | < .001
AE | -0.43 | -0.53, -0.33 | < .001
BR | 1.21 | 0.84, 1.58 | < .001
AR | -1.19e-03 | -0.03, 0.03 | 0.936
=====================================================================
# (Average) Linear trend for Time
Phase | Contrast | 95% CI | p
----------------------------------------
BE-AE | 0.49 | 0.39, 0.59 | < .001
BE-BR | -1.15 | -1.52, -0.78 | < .001
BE-AR | 0.06 | 0.03, 0.09 | < .001
AE-BR | -1.64 | -2.03, -1.26 | < .001
AE-AR | -0.43 | -0.53, -0.33 | < .001
BR-AR | 1.21 | 0.84, 1.58 | < .001
Plot: Basic
Effects: Phase x Outcome
Compute
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
=====================================================================
# Average predicted values of Agency
Outcome: loser
Phase | Predicted | 95% CI
--------------------------------
BE | 0.51 | 0.50, 0.52
AE | 0.50 | 0.48, 0.52
BR | -0.07 | -0.21, 0.08
AR | 0.39 | 0.37, 0.42
Outcome: winner
Phase | Predicted | 95% CI
--------------------------------
BE | 0.53 | 0.53, 0.54
AE | 0.57 | 0.56, 0.59
BR | -0.18 | -0.26, -0.09
AR | 0.57 | 0.56, 0.58
=====================================================================
Phase | Outcome | Predicted | 95% CI | p
---------------------------------------------------
BE | loser | 0.51 | 0.50, 0.52 | < .001
AE | loser | 0.50 | 0.48, 0.52 | < .001
BR | loser | -0.07 | -0.21, 0.08 | 0.364
AR | loser | 0.39 | 0.37, 0.42 | < .001
BE | winner | 0.53 | 0.53, 0.54 | < .001
AE | winner | 0.57 | 0.56, 0.59 | < .001
BR | winner | -0.18 | -0.26, -0.09 | < .001
AR | winner | 0.57 | 0.56, 0.58 | < .001
=====================================================================
# Pairwise comparisons
Phase | Outcome | Contrast | 95% CI | p
--------------------------------------------------------
BE-AE | loser-loser | 9.06e-03 | -0.01, 0.03 | 0.404
BE-BR | loser-loser | 0.57 | 0.43, 0.72 | < .001
BE-AR | loser-loser | 0.12 | 0.09, 0.14 | < .001
BE-BE | loser-winner | -0.03 | -0.04, -0.01 | < .001
BE-AE | loser-winner | -0.06 | -0.08, -0.05 | < .001
BE-BR | loser-winner | 0.69 | 0.60, 0.77 | < .001
BE-AR | loser-winner | -0.06 | -0.08, -0.05 | < .001
AE-BR | loser-loser | 0.57 | 0.42, 0.71 | < .001
AE-AR | loser-loser | 0.11 | 0.08, 0.14 | < .001
AE-BE | loser-winner | -0.03 | -0.06, -0.01 | 0.003
AE-AE | loser-winner | -0.07 | -0.10, -0.05 | < .001
AE-BR | loser-winner | 0.68 | 0.59, 0.76 | < .001
AE-AR | loser-winner | -0.07 | -0.09, -0.04 | < .001
BR-AR | loser-loser | -0.46 | -0.60, -0.31 | < .001
BR-BE | loser-winner | -0.60 | -0.74, -0.46 | < .001
BR-AE | loser-winner | -0.64 | -0.78, -0.49 | < .001
BR-BR | loser-winner | 0.11 | -0.06, 0.28 | 0.205
BR-AR | loser-winner | -0.64 | -0.78, -0.49 | < .001
AR-BE | loser-winner | -0.14 | -0.16, -0.12 | < .001
AR-AE | loser-winner | -0.18 | -0.20, -0.15 | < .001
AR-BR | loser-winner | 0.57 | 0.48, 0.66 | < .001
AR-AR | loser-winner | -0.18 | -0.20, -0.15 | < .001
BE-AE | winner-winner | -0.04 | -0.05, -0.02 | < .001
BE-BR | winner-winner | 0.71 | 0.63, 0.80 | < .001
BE-AR | winner-winner | -0.04 | -0.05, -0.02 | < .001
AE-BR | winner-winner | 0.75 | 0.66, 0.83 | < .001
AE-AR | winner-winner | 2.17e-03 | -0.01, 0.02 | 0.800
BR-AR | winner-winner | -0.75 | -0.83, -0.66 | < .001
Plot: Basic
Effects: Time x Phase x Outcome
Compute
fit04aPh: [df0] Agency ~ (Time | Name) + Time * Phase * Outcome
=====================================================================
# Average predicted values of Agency
Outcome: loser
Phase: BE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.45 | 0.44, 0.46
-0.50 | 0.48 | 0.47, 0.49
0.00 | 0.51 | 0.50, 0.52
0.50 | 0.54 | 0.53, 0.55
1.00 | 0.57 | 0.56, 0.59
Outcome: loser
Phase: AE
Time | Predicted | 95% CI
--------------------------------
-1.00 | 0.90 | 0.79, 1.01
-0.50 | 0.69 | 0.62, 0.75
0.00 | 0.47 | 0.45, 0.49
0.50 | 0.25 | 0.22, 0.29
1.00 | 0.04 | -0.05, 0.13
Outcome: loser
Phase: BR
Time | Predicted | 95% CI
--------------------------------
-1.00 | -1.20 | -1.69, -0.70
-0.50 | -0.59 | -0.89, -0.29
0.00 | 0.02 | -0.10, 0.13
0.50 | 0.62 | 0.55, 0.69
1.00 | 1.23 | 0.97, 1.48
Outcome: loser
Phase: AR
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.39 | 0.34, 0.44
-0.50 | 0.39 | 0.36, 0.43
0.00 | 0.39 | 0.37, 0.41
0.50 | 0.39 | 0.38, 0.40
1.00 | 0.39 | 0.38, 0.41
Outcome: winner
Phase: BE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.50 | 0.49, 0.51
-0.50 | 0.52 | 0.51, 0.52
0.00 | 0.54 | 0.53, 0.54
0.50 | 0.56 | 0.55, 0.57
1.00 | 0.58 | 0.56, 0.59
Outcome: winner
Phase: AE
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.84 | 0.77, 0.90
-0.50 | 0.69 | 0.66, 0.73
0.00 | 0.55 | 0.54, 0.56
0.50 | 0.41 | 0.39, 0.43
1.00 | 0.27 | 0.22, 0.32
Outcome: winner
Phase: BR
Time | Predicted | 95% CI
--------------------------------
-1.00 | -1.87 | -2.16, -1.58
-0.50 | -0.96 | -1.14, -0.78
0.00 | -0.05 | -0.12, 0.02
0.50 | 0.85 | 0.81, 0.90
1.00 | 1.76 | 1.61, 1.91
Outcome: winner
Phase: AR
Time | Predicted | 95% CI
-------------------------------
-1.00 | 0.63 | 0.60, 0.65
-0.50 | 0.60 | 0.58, 0.62
0.00 | 0.56 | 0.55, 0.58
0.50 | 0.53 | 0.53, 0.54
1.00 | 0.50 | 0.49, 0.51
=====================================================================
# (Average) Linear trend for Time
Outcome | Phase | Slope | 95% CI | p
---------------------------------------------------
loser | BE | 0.06 | 0.05, 0.07 | < .001
loser | AE | -0.43 | -0.53, -0.33 | < .001
loser | BR | 1.21 | 0.84, 1.58 | < .001
loser | AR | -1.19e-03 | -0.03, 0.03 | 0.936
winner | BE | 0.04 | 0.03, 0.05 | < .001
winner | AE | -0.29 | -0.35, -0.23 | < .001
winner | BR | 1.81 | 1.59, 2.03 | < .001
winner | AR | -0.07 | -0.08, -0.05 | < .001
=====================================================================
# (Average) Linear trend for Time
Outcome | Phase | Contrast | 95% CI | p
--------------------------------------------------------
loser-loser | BE-AE | 0.49 | 0.39, 0.59 | < .001
loser-loser | BE-BR | -1.15 | -1.52, -0.78 | < .001
loser-loser | BE-AR | 0.06 | 0.03, 0.09 | < .001
loser-winner | BE-BE | 0.02 | 0.01, 0.03 | 0.005
loser-winner | BE-AE | 0.34 | 0.28, 0.40 | < .001
loser-winner | BE-BR | -1.76 | -1.98, -1.54 | < .001
loser-winner | BE-AR | 0.12 | 0.10, 0.14 | < .001
loser-loser | AE-BR | -1.64 | -2.03, -1.26 | < .001
loser-loser | AE-AR | -0.43 | -0.53, -0.33 | < .001
loser-winner | AE-BE | -0.47 | -0.57, -0.37 | < .001
loser-winner | AE-AE | -0.15 | -0.26, -0.03 | 0.013
loser-winner | AE-BR | -2.25 | -2.49, -2.01 | < .001
loser-winner | AE-AR | -0.37 | -0.47, -0.27 | < .001
loser-loser | BR-AR | 1.21 | 0.84, 1.58 | < .001
loser-winner | BR-BE | 1.17 | 0.80, 1.55 | < .001
loser-winner | BR-AE | 1.50 | 1.12, 1.87 | < .001
loser-winner | BR-BR | -0.61 | -1.04, -0.17 | 0.007
loser-winner | BR-AR | 1.28 | 0.90, 1.65 | < .001
loser-winner | AR-BE | -0.04 | -0.07, -0.01 | 0.015
loser-winner | AR-AE | 0.29 | 0.22, 0.35 | < .001
loser-winner | AR-BR | -1.82 | -2.04, -1.59 | < .001
loser-winner | AR-AR | 0.07 | 0.03, 0.10 | < .001
winner-winner | BE-AE | 0.32 | 0.26, 0.38 | < .001
winner-winner | BE-BR | -1.78 | -2.00, -1.56 | < .001
winner-winner | BE-AR | 0.10 | 0.09, 0.12 | < .001
winner-winner | AE-BR | -2.10 | -2.33, -1.87 | < .001
winner-winner | AE-AR | -0.22 | -0.28, -0.16 | < .001
winner-winner | BR-AR | 1.88 | 1.66, 2.10 | < .001
Filter test table
# A tibble: 16 × 7
Time Outcome Phase Contrast conf.low conf.high p.value
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 slope loser-winner AE -0.147 -0.262 -0.0321 1.27e- 2
2 slope loser-winner AR 0.0652 0.0321 0.0982 1.34e- 4
3 slope loser-winner BE 0.0204 0.00628 0.0345 5.18e- 3
4 slope loser-winner BR -0.605 -1.04 -0.172 6.62e- 3
5 slope loser AE-AR -0.432 -0.535 -0.330 2.45e-16
6 slope loser AE-BR -1.64 -2.03 -1.26 1.47e-16
7 slope loser BE-AE 0.491 0.392 0.590 7.06e-22
8 slope loser BE-AR 0.0582 0.0284 0.0881 1.53e- 4
9 slope loser BE-BR -1.15 -1.52 -0.779 1.82e- 9
10 slope loser BR-AR 1.21 0.836 1.58 3.23e-10
11 slope winner AE-AR -0.220 -0.281 -0.160 1.55e-12
12 slope winner AE-BR -2.10 -2.33 -1.87 5.37e-72
13 slope winner BE-AE 0.323 0.264 0.382 2.74e-26
14 slope winner BE-AR 0.103 0.0869 0.119 2.74e-35
15 slope winner BE-BR -1.78 -2.00 -1.56 9.36e-56
16 slope winner BR-AR 1.88 1.66 2.10 7.56e-62
Plot: Basic
Plot: Nicer
Save Workspace
Model fit04xPh: Time x Phase x Outcome
Prepare Data for the Re-scaled Model
[,1] [,2] [,3]
BE 1 0 0
AE 0 1 0
BR 0 0 1
AR -1 -1 -1
[,1]
loser 1
winner -1
Fit
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Data: df8
Control: control
REML criterion at convergence: 23562.2
Scaled residuals:
Min 1Q Median 3Q Max
-8.1902 -0.5632 -0.0074 0.5639 7.3864
Random effects:
Groups Name Variance Std.Dev. Corr
Name (Intercept) 0.004849 0.06963
TimeC 0.003347 0.05786 -0.12
Residual 0.065916 0.25674
Number of obs: 169997, groups: Name, 870
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) -1.430e-01 1.111e-02 1.138e+05 -12.873 < 2e-16 ***
TimeC 2.911e-01 2.871e-02 1.687e+05 10.141 < 2e-16 ***
Phase1 1.673e-01 1.088e-02 1.689e+05 15.372 < 2e-16 ***
Phase2 1.815e-01 1.164e-02 1.688e+05 15.591 < 2e-16 ***
Phase3 -4.760e-01 3.189e-02 1.689e+05 -14.925 < 2e-16 ***
Outcome1 -2.021e-02 1.111e-02 1.138e+05 -1.819 0.06893 .
TimeC:Phase1 -2.443e-01 2.870e-02 1.689e+05 -8.510 < 2e-16 ***
TimeC:Phase2 -6.511e-01 3.535e-02 1.690e+05 -18.419 < 2e-16 ***
TimeC:Phase3 1.220e+00 8.317e-02 1.689e+05 14.671 < 2e-16 ***
TimeC:Outcome1 -8.335e-02 2.871e-02 1.687e+05 -2.904 0.00369 **
Phase1:Outcome1 7.600e-03 1.088e-02 1.689e+05 0.698 0.48496
Phase2:Outcome1 -1.568e-02 1.164e-02 1.688e+05 -1.347 0.17804
Phase3:Outcome1 7.591e-02 3.189e-02 1.689e+05 2.380 0.01730 *
TimeC:Phase1:Outcome1 9.355e-02 2.870e-02 1.689e+05 3.259 0.00112 **
TimeC:Phase2:Outcome1 9.791e-03 3.535e-02 1.690e+05 0.277 0.78180
TimeC:Phase3:Outcome1 -2.193e-01 8.317e-02 1.689e+05 -2.636 0.00838 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# R2 for Mixed Models
Conditional R2: 0.102
Marginal R2: 0.021
---------------------------------------------------------------------
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# Intraclass Correlation Coefficient
Adjusted ICC: 0.083
Unadjusted ICC: 0.081
---------------------------------------------------------------------
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# ICC by Group
Group | ICC
-------------
Name | 0.067
---------------------------------------------------------------------
Performance: Check Model (EXPERIMENTAL)
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Save checks plot
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Performance: Check Collinearity
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Performance: Check Convergence
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
[1] TRUE
attr(,"gradient")
[1] 4.648806e-06
Performance: Check Heteroscedasticity
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Warning: Heteroscedasticity (non-constant error variance) detected (p < .001).
Performance: Check Homogeneity
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Performance: Check Outliers
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
OK: No outliers detected.
- Based on the following method and threshold: cook (0.7).
- For variable: (Whole model)
Performance: Check Overdispersion
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
# Overdispersion test
dispersion ratio = 0.992
p-value = 0.152
Performance: Check Predictions
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Warning: Minimum value of original data is not included in the
replicated data.
Model may not capture the variation of the data.Warning: Maximum value of original data is not included in the
replicated data.
Model may not capture the variation of the data.
Performance: Check Singularity
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
[1] FALSE
Performance: Check Zeroinflation
fit04xPh: [df8] AgencyC ~ (TimeC | Name) + TimeC * Phase * Outcome
Performance
Reclaim Model fit04aPh
fit04aPh
Score
| Comparison of Model Performance Indices | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Name | Model | R2 (cond.) | R2 (marg.) | ICC | RMSE | Sigma | AIC weights | AICc weights | BIC weights | Performance-Score |
| fit04aPh | lmerModLmerTest | 0.10 | 0.02 | 0.08 | 0.26 | 0.26 | 1.00 | 1.00 | 1.00 | 84.61% |
| fit03aPh | lmerModLmerTest | 0.11 | 6.03e-03 | 0.10 | 0.26 | 0.26 | 2.51e-118 | 2.51e-118 | 7.03e-101 | 52.18% |
| fit02aPh | lmerModLmerTest | 0.10 | 4.62e-04 | 0.10 | 0.26 | 0.26 | 9.57e-321 | 9.58e-321 | 3.26e-290 | 40.78% |
| fit01aPh | lmerModLmerTest | 0.08 | 0.00 | 0.08 | 0.26 | 0.26 | 0.00e+00 | 0.00e+00 | 0.00e+00 | 0.99% |
| NA | ||||||||||
Performance Table Sorted by R2_conditional
| Comparison of Model Performance Indices | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Name | Model | R2 (cond.) | R2 (marg.) | ICC | RMSE | Sigma | AIC weights | AICc weights | BIC weights | Performance-Score |
| fit03aPh | lmerModLmerTest | 0.11 | 6.03e-03 | 0.10 | 0.26 | 0.26 | 2.51e-118 | 2.51e-118 | 7.03e-101 | 52.18% |
| fit02aPh | lmerModLmerTest | 0.10 | 4.62e-04 | 0.10 | 0.26 | 0.26 | 9.57e-321 | 9.58e-321 | 3.26e-290 | 40.78% |
| fit04aPh | lmerModLmerTest | 0.10 | 0.02 | 0.08 | 0.26 | 0.26 | 1.00 | 1.00 | 1.00 | 84.61% |
| fit01aPh | lmerModLmerTest | 0.08 | 0.00 | 0.08 | 0.26 | 0.26 | 0.00e+00 | 0.00e+00 | 0.00e+00 | 0.99% |
| NA | ||||||||||
Performance Table Sorted by R2_marginal
| Comparison of Model Performance Indices | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Name | Model | R2 (cond.) | R2 (marg.) | ICC | RMSE | Sigma | AIC weights | AICc weights | BIC weights | Performance-Score |
| fit04aPh | lmerModLmerTest | 0.10 | 0.02 | 0.08 | 0.26 | 0.26 | 1.00 | 1.00 | 1.00 | 84.61% |
| fit03aPh | lmerModLmerTest | 0.11 | 6.03e-03 | 0.10 | 0.26 | 0.26 | 2.51e-118 | 2.51e-118 | 7.03e-101 | 52.18% |
| fit02aPh | lmerModLmerTest | 0.10 | 4.62e-04 | 0.10 | 0.26 | 0.26 | 9.57e-321 | 9.58e-321 | 3.26e-290 | 40.78% |
| fit01aPh | lmerModLmerTest | 0.08 | 0.00 | 0.08 | 0.26 | 0.26 | 0.00e+00 | 0.00e+00 | 0.00e+00 | 0.99% |
| NA | ||||||||||
Interpret R2
weak
weak
Plot models
Tabulate Models
| Model 1 | Model 2 | Model 3 | Model 4 | |||||
|---|---|---|---|---|---|---|---|---|
| Predictors | Estimates | CI | Estimates | CI | Estimates | CI | Estimates | CI |
| (Intercept) | 0.50 *** | 0.49 – 0.50 | 0.50 *** | 0.49 – 0.50 | 0.53 *** | 0.52 – 0.53 | 0.52 *** | 0.51 – 0.52 |
| Time | -0.01 *** | -0.02 – -0.01 | 0.04 *** | 0.04 – 0.05 | 0.06 *** | 0.05 – 0.07 | ||
| Phase [AE] | -0.00 | -0.01 – 0.00 | -0.04 *** | -0.06 – -0.03 | ||||
| Phase [BR] | -0.57 *** | -0.63 – -0.51 | -0.50 *** | -0.61 – -0.38 | ||||
| Phase [AR] | -0.01 | -0.02 – 0.00 | -0.12 *** | -0.14 – -0.10 | ||||
| Time × Phase [AE] | -0.36 *** | -0.41 – -0.31 | -0.49 *** | -0.59 – -0.39 | ||||
| Time × Phase [BR] | 1.61 *** | 1.42 – 1.80 | 1.15 *** | 0.78 – 1.52 | ||||
| Time × Phase [AR] | -0.10 *** | -0.11 – -0.09 | -0.06 *** | -0.09 – -0.03 | ||||
| Outcome [winner] | 0.02 *** | 0.01 – 0.04 | ||||||
| Time × Outcome [winner] | -0.02 ** | -0.03 – -0.01 | ||||||
| Phase [AE] × Outcome [winner] | 0.06 *** | 0.04 – 0.08 | ||||||
| Phase [BR] × Outcome [winner] | -0.09 | -0.23 – 0.04 | ||||||
| Phase [AR] × Outcome [winner] | 0.15 *** | 0.12 – 0.17 | ||||||
| (Time × Phase [AE]) × Outcome [winner] | 0.17 ** | 0.05 – 0.28 | ||||||
| (Time × Phase [BR]) × Outcome [winner] | 0.63 ** | 0.19 – 1.06 | ||||||
| (Time × Phase [AR]) × Outcome [winner] | -0.04 ** | -0.08 – -0.01 | ||||||
| Random Effects | ||||||||
| σ2 | 0.07 | 0.07 | 0.07 | 0.07 | ||||
| τ00 | 0.01 Name | 0.01 Name | 0.01 Name | 0.00 Name | ||||
| τ11 | 0.00 Name.Time | 0.00 Name.Time | 0.00 Name.Time | |||||
| ρ01 | 0.18 Name | 0.18 Name | -0.07 Name | |||||
| ICC | 0.08 | 0.10 | 0.10 | 0.08 | ||||
| N | 870 Name | 870 Name | 870 Name | 870 Name | ||||
| Observations | 169997 | 169997 | 169997 | 169997 | ||||
| Marginal R2 / Conditional R2 | 0.000 / 0.084 | 0.000 / 0.102 | 0.006 / 0.107 | 0.021 / 0.102 | ||||
| * p<0.05 ** p<0.01 *** p<0.001 | ||||||||
./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/summary-tab-model-i0001-base.html
Report fit01aPh
We fitted a constant (intercept-only) linear mixed model (estimated using REML
and Nelder-Mead optimizer) to predict Agency (formula: Agency ~ 1). The model
included Name as random effect (formula: ~1 | Name). The model's intercept is
at 0.50 (95% CI [0.49, 0.50], t(169994) = 177.65, p < .001).
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.
Report fit02aPh
We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time (formula: Agency ~ Time). The model included Time
as random effects (formula: ~Time | Name). The model's total explanatory power
is weak (conditional R2 = 0.10) and the part related to the fixed effects alone
(marginal R2) is of 4.62e-04. The model's intercept, corresponding to Time = 0,
is at 0.50 (95% CI [0.49, 0.50], t(169991) = 174.88, p < .001). Within this
model:
- The effect of Time is statistically significant and negative (beta = -0.01,
95% CI [-0.02, -5.07e-03], t(169991) = -3.88, p < .001; Std. beta = -0.02, 95%
CI [-0.03, -0.01])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.
Report fit03aPh
We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time and Phase (formula: Agency ~ Time * Phase). The
model included Time as random effects (formula: ~Time | Name). The model's
total explanatory power is weak (conditional R2 = 0.11) and the part related to
the fixed effects alone (marginal R2) is of 6.03e-03. The model's intercept,
corresponding to Time = 0 and Phase = BE, is at 0.53 (95% CI [0.52, 0.53],
t(169985) = 166.75, p < .001). Within this model:
- The effect of Time is statistically significant and positive (beta = 0.04,
95% CI [0.04, 0.05], t(169985) = 12.19, p < .001; Std. beta = 0.09, 95% CI
[0.08, 0.11])
- The effect of Phase [AE] is statistically non-significant and negative (beta
= -4.14e-03, 95% CI [-0.01, 4.04e-03], t(169985) = -0.99, p = 0.321; Std. beta
= 0.07, 95% CI [0.03, 0.12])
- The effect of Phase [BR] is statistically significant and negative (beta =
-0.57, 95% CI [-0.63, -0.51], t(169985) = -18.56, p < .001; Std. beta = -2.51,
95% CI [-2.78, -2.24])
- The effect of Phase [AR] is statistically non-significant and negative (beta
= -9.12e-03, 95% CI [-0.02, 5.54e-04], t(169985) = -1.85, p = 0.065; Std. beta
= -8.65e-03, 95% CI [-0.05, 0.03])
- The effect of Time × Phase [AE] is statistically significant and negative
(beta = -0.36, 95% CI [-0.41, -0.31], t(169985) = -13.82, p < .001; Std. beta =
-0.76, 95% CI [-0.86, -0.65])
- The effect of Time × Phase [BR] is statistically significant and positive
(beta = 1.61, 95% CI [1.42, 1.80], t(169985) = 16.65, p < .001; Std. beta =
3.40, 95% CI [3.00, 3.80])
- The effect of Time × Phase [AR] is statistically significant and negative
(beta = -0.10, 95% CI [-0.11, -0.09], t(169985) = -13.81, p < .001; Std. beta =
-0.21, 95% CI [-0.24, -0.18])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.
Report fit04aPh
We fitted a linear mixed model (estimated using REML and Nelder-Mead optimizer)
to predict Agency with Time, Phase and Outcome (formula: Agency ~ Time * Phase
* Outcome). The model included Time as random effects (formula: ~Time | Name).
The model's total explanatory power is weak (conditional R2 = 0.10) and the
part related to the fixed effects alone (marginal R2) is of 0.02. The model's
intercept, corresponding to Time = 0, Phase = BE and Outcome = loser, is at
0.52 (95% CI [0.51, 0.52], t(169977) = 115.77, p < .001). Within this model:
- The effect of Time is statistically significant and positive (beta = 0.06,
95% CI [0.05, 0.07], t(169977) = 10.19, p < .001; Std. beta = 0.12, 95% CI
[0.10, 0.14])
- The effect of Phase [AE] is statistically significant and negative (beta =
-0.04, 95% CI [-0.06, -0.03], t(169977) = -5.52, p < .001; Std. beta = -0.03,
95% CI [-0.11, 0.04])
- The effect of Phase [BR] is statistically significant and negative (beta =
-0.50, 95% CI [-0.61, -0.38], t(169977) = -8.24, p < .001; Std. beta = -2.12,
95% CI [-2.65, -1.60])
- The effect of Phase [AR] is statistically significant and negative (beta =
-0.12, 95% CI [-0.14, -0.10], t(169977) = -11.56, p < .001; Std. beta = -0.43,
95% CI [-0.51, -0.35])
- The effect of Outcome [winner] is statistically significant and positive
(beta = 0.02, 95% CI [0.01, 0.04], t(169977) = 4.07, p < .001; Std. beta =
0.09, 95% CI [0.05, 0.13])
- The effect of Time × Phase [AE] is statistically significant and negative
(beta = -0.49, 95% CI [-0.59, -0.39], t(169977) = -9.71, p < .001; Std. beta =
-1.04, 95% CI [-1.25, -0.83])
- The effect of Time × Phase [BR] is statistically significant and positive
(beta = 1.15, 95% CI [0.78, 1.52], t(169977) = 6.05, p < .001; Std. beta =
2.43, 95% CI [1.64, 3.22])
- The effect of Time × Phase [AR] is statistically significant and negative
(beta = -0.06, 95% CI [-0.09, -0.03], t(169977) = -3.82, p < .001; Std. beta =
-0.12, 95% CI [-0.19, -0.06])
- The effect of Time × Outcome [winner] is statistically significant and
negative (beta = -0.02, 95% CI [-0.03, -6.28e-03], t(169977) = -2.83, p =
0.005; Std. beta = -0.04, 95% CI [-0.07, -0.01])
- The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.06, 95% CI [0.04, 0.08], t(169977) = 6.32, p < .001; Std.
beta = 0.17, 95% CI [0.08, 0.26])
- The effect of Phase [BR] × Outcome [winner] is statistically non-significant
and negative (beta = -0.09, 95% CI [-0.23, 0.04], t(169977) = -1.34, p = 0.179;
Std. beta = -0.50, 95% CI [-1.12, 0.11])
- The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.15, 95% CI [0.12, 0.17], t(169977) = 12.55, p < .001; Std.
beta = 0.56, 95% CI [0.47, 0.65])
- The effect of (Time × Phase [AE]) × Outcome [winner] is statistically
significant and positive (beta = 0.17, 95% CI [0.05, 0.28], t(169977) = 2.85, p
= 0.004; Std. beta = 0.35, 95% CI [0.11, 0.60])
- The effect of (Time × Phase [BR]) × Outcome [winner] is statistically
significant and positive (beta = 0.63, 95% CI [0.19, 1.06], t(169977) = 2.83, p
= 0.005; Std. beta = 1.32, 95% CI [0.41, 2.24])
- The effect of (Time × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.04, 95% CI [-0.08, -0.01], t(169977) =
-2.59, p = 0.010; Std. beta = -0.09, 95% CI [-0.17, -0.02])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald t-distribution approximation.
Save Workspace
glmmTMB Models
[1] 169997 22
[1] 495252 22
[1] 169997 22
[1] 169997 24
# A tibble: 4 × 2
Phase Count
<fct> <int>
1 BE 15000
2 AE 15000
3 BR 15000
4 AR 15000
Model xFit05aPhLikes
Fit
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
Family: truncated_poisson ( log )
Formula: LikeCount ~ Agency * Phase + (1 | Name)
Zero inflation: ~Agency * Phase
Data: df5
AIC BIC logLik deviance df.resid
221541905 221542058 -110770936 221541871 59983
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
Name (Intercept) 4.014 2.004
Number of obs: 60000, groups: Name, 847
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 4.0046334 0.0693135 57.8 <2e-16 ***
Agency -0.1697153 0.0009258 -183.3 <2e-16 ***
PhaseAE 0.6429410 0.0006443 998.0 <2e-16 ***
PhaseBR 0.8824608 0.0006271 1407.3 <2e-16 ***
PhaseAR 0.6342543 0.0006679 949.6 <2e-16 ***
Agency:PhaseAE 0.2389858 0.0010427 229.2 <2e-16 ***
Agency:PhaseBR 0.5147667 0.0010001 514.7 <2e-16 ***
Agency:PhaseAR -0.2984013 0.0011079 -269.3 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Zero-inflation model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.855292 0.063879 -44.70 < 2e-16 ***
Agency -0.977835 0.118416 -8.26 < 2e-16 ***
PhaseAE -0.113788 0.089774 -1.27 0.205
PhaseBR -0.414069 0.091501 -4.53 6.03e-06 ***
PhaseAR -0.645866 0.102981 -6.27 3.57e-10 ***
Agency:PhaseAE -0.116813 0.169961 -0.69 0.492
Agency:PhaseBR 0.003811 0.168690 0.02 0.982
Agency:PhaseAR -0.031403 0.192888 -0.16 0.871
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# R2 for Mixed Models
Conditional R2: 1.000
Marginal R2: 0.044
---------------------------------------------------------------------
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# Intraclass Correlation Coefficient
Adjusted ICC: 1.000
Unadjusted ICC: 0.956
---------------------------------------------------------------------
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
# ICC by Group
Group | ICC
-------------
Name | 1.000
---------------------------------------------------------------------
Effects: Agency x Phase
Compute
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase: BE
Agency | Predicted | 95% CI
------------------------------------
-3 | 641.92 | 377.87, 905.96
-2 | 801.51 | 671.34, 931.69
-1 | 825.26 | 788.61, 861.92
0 | 759.30 | 754.06, 764.54
1 | 663.30 | 660.85, 665.75
2 | 567.26 | 564.88, 569.65
3 | 481.15 | 478.75, 483.55
Phase: AE
Agency | Predicted | 95% CI
-------------------------------------
-3 | 523.50 | 279.92, 767.09
-2 | 911.71 | 748.85, 1074.56
-1 | 1235.52 | 1180.50, 1290.54
0 | 1452.72 | 1443.91, 1461.53
1 | 1609.21 | 1604.20, 1614.22
2 | 1744.24 | 1739.47, 1749.01
3 | 1876.49 | 1871.47, 1881.51
Phase: BR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 403.89 | 271.77, 536.02
-2 | 768.32 | 678.12, 858.53
-1 | 1248.59 | 1210.98, 1286.19
0 | 1869.57 | 1860.72, 1878.41
1 | 2701.55 | 2694.24, 2708.86
2 | 3848.66 | 3839.22, 3858.11
3 | 5452.85 | 5440.57, 5465.13
Phase: AR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 3799.94 | 2328.29, 5271.60
-2 | 3147.04 | 2731.52, 3562.55
-1 | 2233.20 | 2161.09, 2305.31
0 | 1469.78 | 1462.89, 1476.66
1 | 937.80 | 935.39, 940.22
2 | 591.33 | 589.68, 592.98
3 | 371.24 | 370.01, 372.47
=====================================================================
# (Average) Linear trend for Agency
Phase | Slope | 95% CI | p
-------------------------------------------
BE | -7.44 | -34.92, 20.03 | 0.595
AE | 140.58 | 119.62, 161.53 | < .001
BR | 545.42 | 532.83, 558.01 | < .001
AR | -316.07 | -515.36, -116.78 | 0.003
=====================================================================
# (Average) Linear trend for Agency
Phase | Contrast | 95% CI | p
--------------------------------------------
BE-AE | -148.02 | -182.58, -113.46 | < .001
BE-BR | -552.86 | -583.26, -522.46 | < .001
BE-AR | 308.62 | 107.44, 509.80 | 0.003
AE-BR | -404.84 | -429.29, -380.39 | < .001
AE-AR | 456.64 | 256.25, 657.04 | < .001
BR-AR | 861.48 | 661.80, 1061.17 | < .001
Plot: Basic
Effects: Phase
Compute
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase | Predicted | 95% CI
------------------------------------
BE | 711.61 | 709.24, 713.98
AE | 1532.55 | 1528.18, 1536.92
BR | 2273.83 | 2268.29, 2279.36
AR | 1193.63 | 1190.56, 1196.71
=====================================================================
Phase | Predicted | 95% CI | p
---------------------------------------------
BE | 711.61 | 709.24, 713.98 | < .001
AE | 1532.55 | 1528.18, 1536.92 | < .001
BR | 2273.83 | 2268.29, 2279.36 | < .001
AR | 1193.63 | 1190.56, 1196.71 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
----------------------------------------------
BE-AE | -820.94 | -825.93, -815.95 | < .001
BE-BR | -1562.21 | -1568.25, -1556.18 | < .001
BE-AR | -482.02 | -485.91, -478.13 | < .001
AE-BR | -741.27 | -748.35, -734.20 | < .001
AE-AR | 338.92 | 333.56, 344.28 | < .001
BR-AR | 1080.19 | 1073.84, 1086.54 | < .001
Plot: Basic
Effects: Agency
Compute
xFit05aPhLikes: [df5] LikeCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Agency | Predicted | 95% CI
-------------------------------------
-3 | 1275.46 | 920.12, 1630.79
-2 | 1369.84 | 1256.37, 1483.31
-1 | 1390.49 | 1364.03, 1416.95
0 | 1436.86 | 1432.83, 1440.90
1 | 1572.57 | 1569.97, 1575.18
2 | 1833.39 | 1830.35, 1836.43
3 | 2252.68 | 2248.90, 2256.46
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
138.34 | 132.78, 143.90 | < .001
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
138.34 | 132.78, 143.90 | < .001
Plot: Basic
Model xFit06aPhRetweets
Fit
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
Family: truncated_poisson ( log )
Formula: RetweetCount ~ Agency * Phase + (1 | Name)
Zero inflation: ~Agency * Phase
Data: df5
AIC BIC logLik deviance df.resid
38582668 38582821 -19291317 38582634 59983
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
Name (Intercept) 3.22 1.794
Number of obs: 60000, groups: Name, 847
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.052772 0.062654 48.7 <2e-16 ***
Agency -0.291141 0.001850 -157.3 <2e-16 ***
PhaseAE 0.085968 0.001370 62.8 <2e-16 ***
PhaseBR 0.416608 0.001290 322.8 <2e-16 ***
PhaseAR 0.280408 0.001376 203.8 <2e-16 ***
Agency:PhaseAE 0.382094 0.002232 171.2 <2e-16 ***
Agency:PhaseBR 0.543501 0.002082 261.0 <2e-16 ***
Agency:PhaseAR -0.248806 0.002340 -106.3 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Zero-inflation model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.50996 0.05547 -45.25 < 2e-16 ***
Agency -0.65152 0.09842 -6.62 3.6e-11 ***
PhaseAE 0.22469 0.07317 3.07 0.002133 **
PhaseBR 0.09407 0.07190 1.31 0.190749
PhaseAR -0.08184 0.07733 -1.06 0.289903
Agency:PhaseAE -0.44233 0.13470 -3.28 0.001024 **
Agency:PhaseBR -0.32139 0.12936 -2.48 0.012977 *
Agency:PhaseAR -0.53423 0.14284 -3.74 0.000184 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# R2 for Mixed Models
Conditional R2: 1.000
Marginal R2: 0.024
---------------------------------------------------------------------
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# Intraclass Correlation Coefficient
Adjusted ICC: 1.000
Unadjusted ICC: 0.976
---------------------------------------------------------------------
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
# ICC by Group
Group | ICC
-------------
Name | 1.000
---------------------------------------------------------------------
Effects: Agency x Phase
Compute
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of RetweetCount
Phase: BE
Agency | Predicted | 95% CI
-----------------------------------
-3 | 325.22 | 246.14, 404.30
-2 | 294.48 | 262.20, 326.77
-1 | 247.37 | 237.77, 256.98
0 | 197.67 | 196.00, 199.33
1 | 153.27 | 152.39, 154.15
2 | 116.86 | 115.83, 117.89
3 | 88.29 | 87.33, 89.25
Phase: AE
Agency | Predicted | 95% CI
-----------------------------------
-3 | 47.81 | 26.54, 69.09
-2 | 101.82 | 80.97, 122.68
-1 | 163.11 | 153.44, 172.79
0 | 211.40 | 209.55, 213.26
1 | 246.68 | 245.53, 247.82
2 | 276.22 | 274.81, 277.62
3 | 304.80 | 302.84, 306.76
Phase: BR
Agency | Predicted | 95% CI
-----------------------------------
-3 | 57.31 | 37.51, 77.12
-2 | 120.44 | 102.29, 138.59
-1 | 203.74 | 194.70, 212.78
0 | 297.59 | 295.37, 299.81
1 | 403.59 | 401.84, 405.34
2 | 530.20 | 527.81, 532.60
3 | 687.79 | 684.26, 691.31
Phase: AR
Agency | Predicted | 95% CI
-----------------------------------
-3 | 394.14 | 198.99, 589.30
-2 | 462.13 | 362.80, 561.46
-1 | 389.84 | 367.96, 411.72
0 | 263.18 | 261.20, 265.16
1 | 161.20 | 160.56, 161.84
2 | 95.48 | 94.99, 95.97
3 | 56.00 | 55.59, 56.42
=====================================================================
# (Average) Linear trend for Agency
Phase | Slope | 95% CI | p
----------------------------------------
BE | -23.03 | -33.09, -12.97 | < .001
AE | 26.27 | 24.65, 27.88 | < .001
BR | 67.28 | 65.59, 68.98 | < .001
AR | -25.57 | -45.02, -6.11 | 0.010
=====================================================================
# (Average) Linear trend for Agency
Phase | Contrast | 95% CI | p
-------------------------------------------
BE-AE | -49.30 | -59.48, -39.11 | < .001
BE-BR | -90.32 | -100.52, -80.12 | < .001
BE-AR | 2.54 | -19.37, 24.44 | 0.821
AE-BR | -41.02 | -43.36, -38.68 | < .001
AE-AR | 51.83 | 32.31, 71.36 | < .001
BR-AR | 92.85 | 73.32, 112.38 | < .001
Plot: Basic
Effects: Phase
Compute
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of RetweetCount
Phase | Predicted | 95% CI
----------------------------------
BE | 175.12 | 174.36, 175.88
AE | 229.45 | 228.53, 230.38
BR | 349.82 | 348.49, 351.14
AR | 210.27 | 209.41, 211.13
=====================================================================
Phase | Predicted | 95% CI | p
-------------------------------------------
BE | 175.12 | 174.36, 175.88 | < .001
AE | 229.45 | 228.53, 230.38 | < .001
BR | 349.82 | 348.49, 351.14 | < .001
AR | 210.27 | 209.41, 211.13 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
--------------------------------------------
BE-AE | -54.34 | -55.54, -53.13 | < .001
BE-BR | -174.70 | -176.23, -173.16 | < .001
BE-AR | -35.15 | -36.30, -33.99 | < .001
AE-BR | -120.36 | -121.99, -118.73 | < .001
AE-AR | 19.19 | 17.91, 20.46 | < .001
BR-AR | 139.55 | 137.96, 141.14 | < .001
Plot: Basic
Effects: Agency
Compute
xFit06aPhRetweets: [df5] RetweetCount ~ Agency * Phase + (1 | Name)
=====================================================================
# Average predicted counts of RetweetCount
Agency | Predicted | 95% CI
-----------------------------------
-3 | 187.09 | 137.74, 236.44
-2 | 230.25 | 204.71, 255.78
-1 | 244.82 | 238.16, 251.48
0 | 245.36 | 244.37, 246.36
1 | 252.55 | 251.92, 253.18
2 | 274.10 | 273.28, 274.92
3 | 311.92 | 310.75, 313.08
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
---------------------------
7.47 | 6.10, 8.83 | < .001
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
---------------------------
7.47 | 6.10, 8.83 | < .001
Plot: Basic
Model xFit05xPhLikes (+Outcome)
Fit
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Family: truncated_poisson ( log )
Formula: LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Zero inflation: ~Agency * Phase * Outcome
Data: df5
AIC BIC logLik deviance df.resid
220099606 220099903 -110049770 220099540 59967
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
Name (Intercept) 3.629 1.905
Number of obs: 60000, groups: Name, 847
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.403578 0.101509 33.5 < 2e-16 ***
Agency -0.236854 0.001846 -128.3 < 2e-16 ***
PhaseAE 0.558708 0.001422 392.8 < 2e-16 ***
PhaseBR 0.221862 0.001379 160.9 < 2e-16 ***
PhaseAR 0.478180 0.001411 338.8 < 2e-16 ***
Outcomewinner 1.080198 0.133490 8.1 5.87e-16 ***
Agency:PhaseAE 0.618810 0.002383 259.6 < 2e-16 ***
Agency:PhaseBR 0.539332 0.002324 232.1 < 2e-16 ***
Agency:PhaseAR 0.335215 0.002474 135.5 < 2e-16 ***
Agency:Outcomewinner 0.109045 0.002136 51.1 < 2e-16 ***
PhaseAE:Outcomewinner 0.138890 0.001603 86.6 < 2e-16 ***
PhaseBR:Outcomewinner 0.804573 0.001557 516.8 < 2e-16 ***
PhaseAR:Outcomewinner 0.214589 0.001607 133.5 < 2e-16 ***
Agency:PhaseAE:Outcomewinner -0.438193 0.002663 -164.6 < 2e-16 ***
Agency:PhaseBR:Outcomewinner -0.100292 0.002590 -38.7 < 2e-16 ***
Agency:PhaseAR:Outcomewinner -0.728943 0.002776 -262.6 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Zero-inflation model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.30979 0.07459 -30.965 < 2e-16 ***
Agency -1.07909 0.14241 -7.577 3.52e-14 ***
PhaseAE 0.19645 0.10517 1.868 0.061768 .
PhaseBR -0.09359 0.10420 -0.898 0.369091
PhaseAR -0.12255 0.11572 -1.059 0.289585
Outcomewinner -1.36634 0.14790 -9.238 < 2e-16 ***
Agency:PhaseAE 0.59738 0.20263 2.948 0.003197 **
Agency:PhaseBR 0.64089 0.19918 3.218 0.001293 **
Agency:PhaseAR 0.57939 0.22953 2.524 0.011595 *
Agency:Outcomewinner 0.62314 0.26113 2.386 0.017018 *
PhaseAE:Outcomewinner -0.48279 0.20876 -2.313 0.020741 *
PhaseBR:Outcomewinner -1.02919 0.24455 -4.209 2.57e-05 ***
PhaseAR:Outcomewinner -1.22436 0.26595 -4.604 4.15e-06 ***
Agency:PhaseAE:Outcomewinner -1.30315 0.38436 -3.390 0.000698 ***
Agency:PhaseBR:Outcomewinner -1.02597 0.43229 -2.373 0.017629 *
Agency:PhaseAR:Outcomewinner 0.03282 0.44608 0.074 0.941354
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# R2 for Mixed Models
Conditional R2: 1.000
Marginal R2: 0.135
---------------------------------------------------------------------
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# Intraclass Correlation Coefficient
Adjusted ICC: 1.000
Unadjusted ICC: 0.864
---------------------------------------------------------------------
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# ICC by Group
Group | ICC
-------------
Name | 1.000
---------------------------------------------------------------------
Effects: Agency x Outcome x Phase
Compute
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Outcome: loser
Phase: BE
Agency | Predicted | 95% CI
-------------------------------------
-3 | 201.04 | 61.15, 340.92
-2 | 301.03 | 195.73, 406.33
-1 | 341.83 | 277.56, 406.10
0 | 317.06 | 264.40, 369.72
1 | 266.07 | 221.99, 310.15
2 | 214.60 | 179.05, 250.15
3 | 170.64 | 142.37, 198.92
Outcome: loser
Phase: AE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 128.12 | 81.78, 174.45
-2 | 215.61 | 165.83, 265.40
-1 | 347.87 | 286.07, 409.67
0 | 543.67 | 453.24, 634.09
1 | 830.78 | 692.64, 968.92
2 | 1250.42 | 1041.59, 1459.25
3 | 1863.44 | 1552.08, 2174.79
Outcome: loser
Phase: BR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 131.41 | 94.21, 168.60
-2 | 195.24 | 155.93, 234.54
-1 | 282.03 | 233.54, 330.51
0 | 399.03 | 332.79, 465.26
1 | 556.32 | 463.96, 648.69
2 | 767.83 | 639.96, 895.70
3 | 1052.57 | 877.14, 1228.01
Outcome: loser
Phase: AR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 300.42 | 189.72, 411.11
-2 | 372.86 | 287.65, 458.06
-1 | 445.11 | 366.72, 523.50
0 | 516.82 | 430.94, 602.70
1 | 588.94 | 491.03, 686.85
2 | 663.01 | 552.41, 773.60
3 | 740.65 | 617.08, 864.23
Outcome: winner
Phase: BE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1369.93 | 1142.44, 1597.43
-2 | 1246.86 | 1103.20, 1390.52
-1 | 1121.62 | 1010.27, 1232.96
0 | 1001.13 | 904.77, 1097.49
1 | 889.06 | 803.57, 974.54
2 | 786.94 | 711.13, 862.76
3 | 695.09 | 628.05, 762.13
Outcome: winner
Phase: AE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1086.11 | 407.69, 1764.54
-2 | 1553.74 | 1229.15, 1878.32
-1 | 1843.99 | 1653.02, 2034.95
0 | 2023.62 | 1829.03, 2218.22
1 | 2161.07 | 1953.45, 2368.68
2 | 2287.55 | 2067.78, 2507.32
3 | 2414.68 | 2182.67, 2646.70
Outcome: winner
Phase: BR
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1021.33 | 797.64, 1245.01
-2 | 1472.20 | 1302.50, 1641.90
-1 | 2059.39 | 1858.55, 2260.23
0 | 2841.58 | 2568.52, 3114.63
1 | 3897.16 | 3522.79, 4271.53
2 | 5330.76 | 4818.65, 5842.87
3 | 7283.38 | 6583.64, 7983.12
Outcome: winner
Phase: AR
Agency | Predicted | 95% CI
--------------------------------------
-3 | 9770.76 | 8827.19, 10714.34
-2 | 5795.98 | 5237.25, 6354.70
-1 | 3437.75 | 3106.96, 3768.54
0 | 2038.75 | 1842.85, 2234.64
1 | 1208.88 | 1092.72, 1325.04
2 | 716.68 | 647.58, 785.78
3 | 424.80 | 383.42, 466.17
=====================================================================
# (Average) Linear trend for Agency
Outcome | Phase | Slope | 95% CI | p
--------------------------------------------------------
loser | BE | 0.34 | -12.53, 13.21 | 0.959
loser | AE | 207.36 | 176.49, 238.24 | < .001
loser | BR | 107.53 | 91.27, 123.78 | < .001
loser | AR | 49.60 | 34.97, 64.23 | < .001
winner | BE | -74.49 | -101.95, -47.03 | < .001
winner | AE | 160.46 | 79.70, 241.21 | < .001
winner | BR | 734.46 | 643.30, 825.62 | < .001
winner | AR | -1173.57 | -1313.32, -1033.82 | < .001
=====================================================================
# (Average) Linear trend for Agency
Outcome | Phase | Contrast | 95% CI | p
------------------------------------------------------------
loser-loser | BE-AE | -207.03 | -240.43, -173.62 | < .001
loser-loser | BE-BR | -107.19 | -127.89, -86.48 | < .001
loser-loser | BE-AR | -49.26 | -68.73, -29.79 | < .001
loser-winner | BE-BE | 74.83 | 44.52, 105.14 | < .001
loser-winner | BE-AE | -160.12 | -241.90, -78.33 | < .001
loser-winner | BE-BR | -734.12 | -826.22, -642.01 | < .001
loser-winner | BE-AR | 1173.91 | 1033.60, 1314.22 | < .001
loser-loser | AE-BR | 99.84 | 82.39, 117.29 | < .001
loser-loser | AE-AR | 157.77 | 130.45, 185.08 | < .001
loser-winner | AE-BE | 281.86 | 247.46, 316.25 | < .001
loser-winner | AE-AE | 46.91 | -45.85, 139.67 | 0.322
loser-winner | AE-BR | -527.09 | -647.23, -406.96 | < .001
loser-winner | AE-AR | 1380.94 | 1270.35, 1491.52 | < .001
loser-loser | BR-AR | 57.93 | 41.81, 74.05 | < .001
loser-winner | BR-BE | 182.02 | 154.70, 209.34 | < .001
loser-winner | BR-AE | -52.93 | -138.79, 32.93 | 0.235
loser-winner | BR-BR | -626.93 | -733.02, -520.84 | < .001
loser-winner | BR-AR | 1281.10 | 1156.54, 1405.65 | < .001
loser-winner | AR-BE | 124.09 | 95.06, 153.12 | < .001
loser-winner | AR-AE | -110.86 | -194.56, -27.15 | 0.010
loser-winner | AR-BR | -684.86 | -783.65, -586.06 | < .001
loser-winner | AR-AR | 1223.17 | 1089.89, 1356.46 | < .001
winner-winner | BE-AE | -234.95 | -322.20, -147.70 | < .001
winner-winner | BE-BR | -808.95 | -911.92, -705.97 | < .001
winner-winner | BE-AR | 1099.08 | 965.61, 1232.55 | < .001
winner-winner | AE-BR | -574.00 | -681.31, -466.69 | < .001
winner-winner | AE-AR | 1334.03 | 1156.97, 1511.08 | < .001
winner-winner | BR-AR | 1908.03 | 1679.82, 2136.24 | < .001
Plot: Basic
Effects: Phase x Outcome
Compute
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Outcome: loser
Phase | Predicted | 95% CI
------------------------------------
BE | 293.00 | 244.73, 341.26
AE | 675.67 | 561.96, 789.37
BR | 471.96 | 392.83, 551.09
AR | 551.20 | 459.36, 643.03
Outcome: winner
Phase | Predicted | 95% CI
------------------------------------
BE | 947.18 | 855.53, 1038.83
AE | 2090.05 | 1890.03, 2290.06
BR | 3330.59 | 3016.62, 3644.56
AR | 1623.61 | 1462.93, 1784.29
=====================================================================
Phase | Outcome | Predicted | 95% CI | p
-------------------------------------------------------
BE | loser | 293.00 | 244.73, 341.26 | < .001
AE | loser | 675.67 | 561.96, 789.37 | < .001
BR | loser | 471.96 | 392.83, 551.09 | < .001
AR | loser | 551.20 | 459.36, 643.03 | < .001
BE | winner | 947.18 | 855.53, 1038.83 | < .001
AE | winner | 2090.05 | 1890.03, 2290.06 | < .001
BR | winner | 3330.59 | 3016.62, 3644.56 | < .001
AR | winner | 1623.61 | 1462.93, 1784.29 | < .001
=====================================================================
# Pairwise comparisons
Phase | Outcome | Contrast | 95% CI | p
--------------------------------------------------------------
BE-AE | loser-loser | -382.67 | -448.34, -317.00 | < .001
BE-BR | loser-loser | -178.96 | -210.09, -147.84 | < .001
BE-AR | loser-loser | -258.20 | -302.04, -214.36 | < .001
BE-BE | loser-winner | -654.18 | -794.06, -514.31 | < .001
BE-AE | loser-winner | -1797.05 | -2045.29, -1548.81 | < .001
BE-BR | loser-winner | -3037.60 | -3399.79, -2675.40 | < .001
BE-AR | loser-winner | -1330.62 | -1539.52, -1121.71 | < .001
AE-BR | loser-loser | 203.71 | 168.33, 239.08 | < .001
AE-AR | loser-loser | 124.47 | 100.92, 148.01 | < .001
AE-BE | loser-winner | -271.51 | -476.75, -66.27 | 0.010
AE-AE | loser-winner | -1414.38 | -1727.95, -1100.81 | < .001
AE-BR | loser-winner | -2654.93 | -3082.44, -2227.41 | < .001
AE-AR | loser-winner | -947.95 | -1222.20, -673.69 | < .001
BR-AR | loser-loser | -79.24 | -93.57, -64.90 | < .001
BR-BE | loser-winner | -475.22 | -645.92, -304.52 | < .001
BR-AE | loser-winner | -1618.09 | -1897.15, -1339.03 | < .001
BR-BR | loser-winner | -2858.63 | -3251.65, -2465.62 | < .001
BR-AR | loser-winner | -1151.65 | -1391.39, -911.92 | < .001
AR-BE | loser-winner | -395.98 | -579.36, -212.61 | < .001
AR-AE | loser-winner | -1538.85 | -1830.57, -1247.13 | < .001
AR-BR | loser-winner | -2779.40 | -3185.06, -2373.73 | < .001
AR-AR | loser-winner | -1072.42 | -1324.82, -820.02 | < .001
BE-AE | winner-winner | -1142.87 | -1251.37, -1034.37 | < .001
BE-BR | winner-winner | -2383.41 | -2605.82, -2161.01 | < .001
BE-AR | winner-winner | -676.43 | -745.61, -607.26 | < .001
AE-BR | winner-winner | -1240.55 | -1354.71, -1126.38 | < .001
AE-AR | winner-winner | 466.43 | 426.78, 506.09 | < .001
BR-AR | winner-winner | 1706.98 | 1553.60, 1860.36 | < .001
Plot: Basic
Effects: Agency x Phase
Compute
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase: BE
Agency | Predicted | 95% CI
------------------------------------
-3 | 940.79 | 813.19, 1068.40
-2 | 899.62 | 838.94, 960.29
-1 | 835.33 | 814.31, 856.36
0 | 749.99 | 745.70, 754.28
1 | 660.34 | 657.71, 662.96
2 | 576.82 | 573.02, 580.61
3 | 502.55 | 498.62, 506.47
Phase: AE
Agency | Predicted | 95% CI
-------------------------------------
-3 | 734.40 | 309.89, 1158.92
-2 | 1062.47 | 879.60, 1245.34
-1 | 1294.72 | 1248.78, 1340.65
0 | 1480.29 | 1473.50, 1487.07
1 | 1672.68 | 1667.18, 1678.17
2 | 1906.79 | 1896.31, 1917.26
3 | 2212.30 | 2196.46, 2228.15
Phase: BR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 694.61 | 566.90, 822.31
-2 | 1003.39 | 943.44, 1063.33
-1 | 1406.87 | 1384.31, 1429.42
0 | 1944.84 | 1939.27, 1950.41
1 | 2670.63 | 2665.84, 2675.42
2 | 3655.56 | 3647.34, 3663.79
3 | 4995.85 | 4983.38, 5008.33
Phase: AR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 6293.90 | 6221.99, 6365.80
-2 | 3804.98 | 3767.93, 3842.03
-1 | 2339.06 | 2323.11, 2355.01
0 | 1480.00 | 1475.61, 1484.39
1 | 981.28 | 977.40, 985.17
2 | 696.97 | 690.73, 703.22
3 | 540.76 | 533.67, 547.84
=====================================================================
# (Average) Linear trend for Agency
Phase | Slope | 95% CI | p
----------------------------------------
BE | 0.34 | -12.53, 13.21 | 0.959
AE | 207.36 | 176.49, 238.24 | < .001
BR | 107.53 | 91.27, 123.78 | < .001
AR | 49.60 | 34.97, 64.23 | < .001
=====================================================================
# (Average) Linear trend for Agency
Phase | Contrast | 95% CI | p
--------------------------------------------
BE-AE | -207.03 | -240.43, -173.62 | < .001
BE-BR | -107.19 | -127.89, -86.48 | < .001
BE-AR | -49.26 | -68.73, -29.79 | < .001
AE-BR | 99.84 | 82.39, 117.29 | < .001
AE-AR | 157.77 | 130.45, 185.08 | < .001
BR-AR | 57.93 | 41.81, 74.05 | < .001
Plot: Basic
Effects: Phase
Compute
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase | Predicted | 95% CI
------------------------------------
BE | 705.67 | 703.64, 707.71
AE | 1567.55 | 1563.90, 1571.19
BR | 2300.50 | 2297.19, 2303.81
AR | 1210.33 | 1207.77, 1212.89
=====================================================================
Phase | Predicted | 95% CI | p
---------------------------------------------
BE | 705.67 | 703.64, 707.71 | < .001
AE | 1567.55 | 1563.90, 1571.19 | < .001
BR | 2300.50 | 2297.19, 2303.81 | < .001
AR | 1210.33 | 1207.77, 1212.89 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
----------------------------------------------
BE-AE | -861.87 | -866.06, -857.69 | < .001
BE-BR | -1594.83 | -1598.73, -1590.92 | < .001
BE-AR | -504.66 | -507.94, -501.38 | < .001
AE-BR | -732.95 | -737.91, -728.00 | < .001
AE-AR | 357.21 | 352.74, 361.69 | < .001
BR-AR | 1090.17 | 1085.95, 1094.38 | < .001
Plot: Basic
Effects: Agency
Compute
xFit05xPhLikes: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Agency | Predicted | 95% CI
-------------------------------------
-3 | 2097.24 | 1958.79, 2235.70
-2 | 1679.69 | 1618.88, 1740.49
-1 | 1495.51 | 1479.04, 1511.97
0 | 1469.94 | 1467.14, 1472.73
1 | 1579.21 | 1577.17, 1581.25
2 | 1820.50 | 1817.07, 1823.92
3 | 2207.40 | 2202.46, 2212.34
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
110.86 | 106.83, 114.90 | < .001
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
110.86 | 106.83, 114.90 | < .001
Plot: Basic
Model xFit06xPhRetweets (+Outcome)
Fit
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Family: truncated_poisson ( log )
Formula: LikeCount ~ Agency * Phase * Outcome + (1 | Name)
Zero inflation: ~Agency * Phase * Outcome
Data: df5
AIC BIC logLik deviance df.resid
220099606 220099903 -110049770 220099540 59967
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
Name (Intercept) 3.629 1.905
Number of obs: 60000, groups: Name, 847
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.403578 0.101509 33.5 < 2e-16 ***
Agency -0.236854 0.001846 -128.3 < 2e-16 ***
PhaseAE 0.558708 0.001422 392.8 < 2e-16 ***
PhaseBR 0.221862 0.001379 160.9 < 2e-16 ***
PhaseAR 0.478180 0.001411 338.8 < 2e-16 ***
Outcomewinner 1.080198 0.133490 8.1 5.87e-16 ***
Agency:PhaseAE 0.618810 0.002383 259.6 < 2e-16 ***
Agency:PhaseBR 0.539332 0.002324 232.1 < 2e-16 ***
Agency:PhaseAR 0.335215 0.002474 135.5 < 2e-16 ***
Agency:Outcomewinner 0.109045 0.002136 51.1 < 2e-16 ***
PhaseAE:Outcomewinner 0.138890 0.001603 86.6 < 2e-16 ***
PhaseBR:Outcomewinner 0.804573 0.001557 516.8 < 2e-16 ***
PhaseAR:Outcomewinner 0.214589 0.001607 133.5 < 2e-16 ***
Agency:PhaseAE:Outcomewinner -0.438193 0.002663 -164.6 < 2e-16 ***
Agency:PhaseBR:Outcomewinner -0.100292 0.002590 -38.7 < 2e-16 ***
Agency:PhaseAR:Outcomewinner -0.728943 0.002776 -262.6 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Zero-inflation model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -2.30979 0.07459 -30.965 < 2e-16 ***
Agency -1.07909 0.14241 -7.577 3.52e-14 ***
PhaseAE 0.19645 0.10517 1.868 0.061768 .
PhaseBR -0.09359 0.10420 -0.898 0.369091
PhaseAR -0.12255 0.11572 -1.059 0.289585
Outcomewinner -1.36634 0.14790 -9.238 < 2e-16 ***
Agency:PhaseAE 0.59738 0.20263 2.948 0.003197 **
Agency:PhaseBR 0.64089 0.19918 3.218 0.001293 **
Agency:PhaseAR 0.57939 0.22953 2.524 0.011595 *
Agency:Outcomewinner 0.62314 0.26113 2.386 0.017018 *
PhaseAE:Outcomewinner -0.48279 0.20876 -2.313 0.020741 *
PhaseBR:Outcomewinner -1.02919 0.24455 -4.209 2.57e-05 ***
PhaseAR:Outcomewinner -1.22436 0.26595 -4.604 4.15e-06 ***
Agency:PhaseAE:Outcomewinner -1.30315 0.38436 -3.390 0.000698 ***
Agency:PhaseBR:Outcomewinner -1.02597 0.43229 -2.373 0.017629 *
Agency:PhaseAR:Outcomewinner 0.03282 0.44608 0.074 0.941354
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# R2 for Mixed Models
Conditional R2: 1.000
Marginal R2: 0.135
---------------------------------------------------------------------
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# Intraclass Correlation Coefficient
Adjusted ICC: 1.000
Unadjusted ICC: 0.864
---------------------------------------------------------------------
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
# ICC by Group
Group | ICC
-------------
Name | 1.000
---------------------------------------------------------------------
Effects: Agency x Outcome x Phase
Compute
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Outcome: loser
Phase: BE
Agency | Predicted | 95% CI
-------------------------------------
-3 | 201.04 | 61.15, 340.92
-2 | 301.03 | 195.73, 406.33
-1 | 341.83 | 277.56, 406.10
0 | 317.06 | 264.40, 369.72
1 | 266.07 | 221.99, 310.15
2 | 214.60 | 179.05, 250.15
3 | 170.64 | 142.37, 198.92
Outcome: loser
Phase: AE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 128.12 | 81.78, 174.45
-2 | 215.61 | 165.83, 265.40
-1 | 347.87 | 286.07, 409.67
0 | 543.67 | 453.24, 634.09
1 | 830.78 | 692.64, 968.92
2 | 1250.42 | 1041.59, 1459.25
3 | 1863.44 | 1552.08, 2174.79
Outcome: loser
Phase: BR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 131.41 | 94.21, 168.60
-2 | 195.24 | 155.93, 234.54
-1 | 282.03 | 233.54, 330.51
0 | 399.03 | 332.79, 465.26
1 | 556.32 | 463.96, 648.69
2 | 767.83 | 639.96, 895.70
3 | 1052.57 | 877.14, 1228.01
Outcome: loser
Phase: AR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 300.42 | 189.72, 411.11
-2 | 372.86 | 287.65, 458.06
-1 | 445.11 | 366.72, 523.50
0 | 516.82 | 430.94, 602.70
1 | 588.94 | 491.03, 686.85
2 | 663.01 | 552.41, 773.60
3 | 740.65 | 617.08, 864.23
Outcome: winner
Phase: BE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1369.93 | 1142.44, 1597.43
-2 | 1246.86 | 1103.20, 1390.52
-1 | 1121.62 | 1010.27, 1232.96
0 | 1001.13 | 904.77, 1097.49
1 | 889.06 | 803.57, 974.54
2 | 786.94 | 711.13, 862.76
3 | 695.09 | 628.05, 762.13
Outcome: winner
Phase: AE
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1086.11 | 407.69, 1764.54
-2 | 1553.74 | 1229.15, 1878.32
-1 | 1843.99 | 1653.02, 2034.95
0 | 2023.62 | 1829.03, 2218.22
1 | 2161.07 | 1953.45, 2368.68
2 | 2287.55 | 2067.78, 2507.32
3 | 2414.68 | 2182.67, 2646.70
Outcome: winner
Phase: BR
Agency | Predicted | 95% CI
--------------------------------------
-3 | 1021.33 | 797.64, 1245.01
-2 | 1472.20 | 1302.50, 1641.90
-1 | 2059.39 | 1858.55, 2260.23
0 | 2841.58 | 2568.52, 3114.63
1 | 3897.16 | 3522.79, 4271.53
2 | 5330.76 | 4818.65, 5842.87
3 | 7283.38 | 6583.64, 7983.12
Outcome: winner
Phase: AR
Agency | Predicted | 95% CI
--------------------------------------
-3 | 9770.76 | 8827.19, 10714.34
-2 | 5795.98 | 5237.25, 6354.70
-1 | 3437.75 | 3106.96, 3768.54
0 | 2038.75 | 1842.85, 2234.64
1 | 1208.88 | 1092.72, 1325.04
2 | 716.68 | 647.58, 785.78
3 | 424.80 | 383.42, 466.17
=====================================================================
# (Average) Linear trend for Agency
Outcome | Phase | Slope | 95% CI | p
--------------------------------------------------------
loser | BE | 0.34 | -12.53, 13.21 | 0.959
loser | AE | 207.36 | 176.49, 238.24 | < .001
loser | BR | 107.53 | 91.27, 123.78 | < .001
loser | AR | 49.60 | 34.97, 64.23 | < .001
winner | BE | -74.49 | -101.95, -47.03 | < .001
winner | AE | 160.46 | 79.70, 241.21 | < .001
winner | BR | 734.46 | 643.30, 825.62 | < .001
winner | AR | -1173.57 | -1313.32, -1033.82 | < .001
=====================================================================
# (Average) Linear trend for Agency
Outcome | Phase | Contrast | 95% CI | p
------------------------------------------------------------
loser-loser | BE-AE | -207.03 | -240.43, -173.62 | < .001
loser-loser | BE-BR | -107.19 | -127.89, -86.48 | < .001
loser-loser | BE-AR | -49.26 | -68.73, -29.79 | < .001
loser-winner | BE-BE | 74.83 | 44.52, 105.14 | < .001
loser-winner | BE-AE | -160.12 | -241.90, -78.33 | < .001
loser-winner | BE-BR | -734.12 | -826.22, -642.01 | < .001
loser-winner | BE-AR | 1173.91 | 1033.60, 1314.22 | < .001
loser-loser | AE-BR | 99.84 | 82.39, 117.29 | < .001
loser-loser | AE-AR | 157.77 | 130.45, 185.08 | < .001
loser-winner | AE-BE | 281.86 | 247.46, 316.25 | < .001
loser-winner | AE-AE | 46.91 | -45.85, 139.67 | 0.322
loser-winner | AE-BR | -527.09 | -647.23, -406.96 | < .001
loser-winner | AE-AR | 1380.94 | 1270.35, 1491.52 | < .001
loser-loser | BR-AR | 57.93 | 41.81, 74.05 | < .001
loser-winner | BR-BE | 182.02 | 154.70, 209.34 | < .001
loser-winner | BR-AE | -52.93 | -138.79, 32.93 | 0.235
loser-winner | BR-BR | -626.93 | -733.02, -520.84 | < .001
loser-winner | BR-AR | 1281.10 | 1156.54, 1405.65 | < .001
loser-winner | AR-BE | 124.09 | 95.06, 153.12 | < .001
loser-winner | AR-AE | -110.86 | -194.56, -27.15 | 0.010
loser-winner | AR-BR | -684.86 | -783.65, -586.06 | < .001
loser-winner | AR-AR | 1223.17 | 1089.89, 1356.46 | < .001
winner-winner | BE-AE | -234.95 | -322.20, -147.70 | < .001
winner-winner | BE-BR | -808.95 | -911.92, -705.97 | < .001
winner-winner | BE-AR | 1099.08 | 965.61, 1232.55 | < .001
winner-winner | AE-BR | -574.00 | -681.31, -466.69 | < .001
winner-winner | AE-AR | 1334.03 | 1156.97, 1511.08 | < .001
winner-winner | BR-AR | 1908.03 | 1679.82, 2136.24 | < .001
Plot: Basic
Effects: Phase x Outcome
Compute
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Outcome: loser
Phase | Predicted | 95% CI
------------------------------------
BE | 293.00 | 244.73, 341.26
AE | 675.67 | 561.96, 789.37
BR | 471.96 | 392.83, 551.09
AR | 551.20 | 459.36, 643.03
Outcome: winner
Phase | Predicted | 95% CI
------------------------------------
BE | 947.18 | 855.53, 1038.83
AE | 2090.05 | 1890.03, 2290.06
BR | 3330.59 | 3016.62, 3644.56
AR | 1623.61 | 1462.93, 1784.29
=====================================================================
Phase | Outcome | Predicted | 95% CI | p
-------------------------------------------------------
BE | loser | 293.00 | 244.73, 341.26 | < .001
AE | loser | 675.67 | 561.96, 789.37 | < .001
BR | loser | 471.96 | 392.83, 551.09 | < .001
AR | loser | 551.20 | 459.36, 643.03 | < .001
BE | winner | 947.18 | 855.53, 1038.83 | < .001
AE | winner | 2090.05 | 1890.03, 2290.06 | < .001
BR | winner | 3330.59 | 3016.62, 3644.56 | < .001
AR | winner | 1623.61 | 1462.93, 1784.29 | < .001
=====================================================================
# Pairwise comparisons
Phase | Outcome | Contrast | 95% CI | p
--------------------------------------------------------------
BE-AE | loser-loser | -382.67 | -448.34, -317.00 | < .001
BE-BR | loser-loser | -178.96 | -210.09, -147.84 | < .001
BE-AR | loser-loser | -258.20 | -302.04, -214.36 | < .001
BE-BE | loser-winner | -654.18 | -794.06, -514.31 | < .001
BE-AE | loser-winner | -1797.05 | -2045.29, -1548.81 | < .001
BE-BR | loser-winner | -3037.60 | -3399.79, -2675.40 | < .001
BE-AR | loser-winner | -1330.62 | -1539.52, -1121.71 | < .001
AE-BR | loser-loser | 203.71 | 168.33, 239.08 | < .001
AE-AR | loser-loser | 124.47 | 100.92, 148.01 | < .001
AE-BE | loser-winner | -271.51 | -476.75, -66.27 | 0.010
AE-AE | loser-winner | -1414.38 | -1727.95, -1100.81 | < .001
AE-BR | loser-winner | -2654.93 | -3082.44, -2227.41 | < .001
AE-AR | loser-winner | -947.95 | -1222.20, -673.69 | < .001
BR-AR | loser-loser | -79.24 | -93.57, -64.90 | < .001
BR-BE | loser-winner | -475.22 | -645.92, -304.52 | < .001
BR-AE | loser-winner | -1618.09 | -1897.15, -1339.03 | < .001
BR-BR | loser-winner | -2858.63 | -3251.65, -2465.62 | < .001
BR-AR | loser-winner | -1151.65 | -1391.39, -911.92 | < .001
AR-BE | loser-winner | -395.98 | -579.36, -212.61 | < .001
AR-AE | loser-winner | -1538.85 | -1830.57, -1247.13 | < .001
AR-BR | loser-winner | -2779.40 | -3185.06, -2373.73 | < .001
AR-AR | loser-winner | -1072.42 | -1324.82, -820.02 | < .001
BE-AE | winner-winner | -1142.87 | -1251.37, -1034.37 | < .001
BE-BR | winner-winner | -2383.41 | -2605.82, -2161.01 | < .001
BE-AR | winner-winner | -676.43 | -745.61, -607.26 | < .001
AE-BR | winner-winner | -1240.55 | -1354.71, -1126.38 | < .001
AE-AR | winner-winner | 466.43 | 426.78, 506.09 | < .001
BR-AR | winner-winner | 1706.98 | 1553.60, 1860.36 | < .001
Plot: Basic
Effects: Agency x Phase
Compute
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase: BE
Agency | Predicted | 95% CI
------------------------------------
-3 | 940.79 | 813.19, 1068.40
-2 | 899.62 | 838.94, 960.29
-1 | 835.33 | 814.31, 856.36
0 | 749.99 | 745.70, 754.28
1 | 660.34 | 657.71, 662.96
2 | 576.82 | 573.02, 580.61
3 | 502.55 | 498.62, 506.47
Phase: AE
Agency | Predicted | 95% CI
-------------------------------------
-3 | 734.40 | 309.89, 1158.92
-2 | 1062.47 | 879.60, 1245.34
-1 | 1294.72 | 1248.78, 1340.65
0 | 1480.29 | 1473.50, 1487.07
1 | 1672.68 | 1667.18, 1678.17
2 | 1906.79 | 1896.31, 1917.26
3 | 2212.30 | 2196.46, 2228.15
Phase: BR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 694.61 | 566.90, 822.31
-2 | 1003.39 | 943.44, 1063.33
-1 | 1406.87 | 1384.31, 1429.42
0 | 1944.84 | 1939.27, 1950.41
1 | 2670.63 | 2665.84, 2675.42
2 | 3655.56 | 3647.34, 3663.79
3 | 4995.85 | 4983.38, 5008.33
Phase: AR
Agency | Predicted | 95% CI
-------------------------------------
-3 | 6293.90 | 6221.99, 6365.80
-2 | 3804.98 | 3767.93, 3842.03
-1 | 2339.06 | 2323.11, 2355.01
0 | 1480.00 | 1475.61, 1484.39
1 | 981.28 | 977.40, 985.17
2 | 696.97 | 690.73, 703.22
3 | 540.76 | 533.67, 547.84
=====================================================================
# (Average) Linear trend for Agency
Phase | Slope | 95% CI | p
----------------------------------------
BE | 0.34 | -12.53, 13.21 | 0.959
AE | 207.36 | 176.49, 238.24 | < .001
BR | 107.53 | 91.27, 123.78 | < .001
AR | 49.60 | 34.97, 64.23 | < .001
=====================================================================
# (Average) Linear trend for Agency
Phase | Contrast | 95% CI | p
--------------------------------------------
BE-AE | -207.03 | -240.43, -173.62 | < .001
BE-BR | -107.19 | -127.89, -86.48 | < .001
BE-AR | -49.26 | -68.73, -29.79 | < .001
AE-BR | 99.84 | 82.39, 117.29 | < .001
AE-AR | 157.77 | 130.45, 185.08 | < .001
BR-AR | 57.93 | 41.81, 74.05 | < .001
Plot: Basic
Effects: Phase
Compute
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Phase | Predicted | 95% CI
------------------------------------
BE | 705.67 | 703.64, 707.71
AE | 1567.55 | 1563.90, 1571.19
BR | 2300.50 | 2297.19, 2303.81
AR | 1210.33 | 1207.77, 1212.89
=====================================================================
Phase | Predicted | 95% CI | p
---------------------------------------------
BE | 705.67 | 703.64, 707.71 | < .001
AE | 1567.55 | 1563.90, 1571.19 | < .001
BR | 2300.50 | 2297.19, 2303.81 | < .001
AR | 1210.33 | 1207.77, 1212.89 | < .001
=====================================================================
# Pairwise comparisons
Phase | Contrast | 95% CI | p
----------------------------------------------
BE-AE | -861.87 | -866.06, -857.69 | < .001
BE-BR | -1594.83 | -1598.73, -1590.92 | < .001
BE-AR | -504.66 | -507.94, -501.38 | < .001
AE-BR | -732.95 | -737.91, -728.00 | < .001
AE-AR | 357.21 | 352.74, 361.69 | < .001
BR-AR | 1090.17 | 1085.95, 1094.38 | < .001
Plot: Basic
Effects: Agency
Compute
xFit06xPhRetweets: [df5] LikeCount ~ Agency * Phase * Outcome + (1 | Name)
=====================================================================
# Average predicted counts of LikeCount
Agency | Predicted | 95% CI
-------------------------------------
-3 | 2097.24 | 1958.79, 2235.70
-2 | 1679.69 | 1618.88, 1740.49
-1 | 1495.51 | 1479.04, 1511.97
0 | 1469.94 | 1467.14, 1472.73
1 | 1579.21 | 1577.17, 1581.25
2 | 1820.50 | 1817.07, 1823.92
3 | 2207.40 | 2202.46, 2212.34
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
110.86 | 106.83, 114.90 | < .001
=====================================================================
# (Average) Linear trend for Agency
Slope | 95% CI | p
--------------------------------
110.86 | 106.83, 114.90 | < .001
Plot: Basic
Tabulate glmmTMB Models
| Like Count | Retweet Count | |||
|---|---|---|---|---|
| Predictors | Incidence Rate Ratios | CI | Incidence Rate Ratios | CI |
| (Intercept) | 54.85 *** | 47.88 – 62.83 | 21.17 *** | 18.73 – 23.94 |
| Agency | 0.84 *** | 0.84 – 0.85 | 0.75 *** | 0.74 – 0.75 |
| Phase [AE] | 1.90 *** | 1.90 – 1.90 | 1.09 *** | 1.09 – 1.09 |
| Phase [BR] | 2.42 *** | 2.41 – 2.42 | 1.52 *** | 1.51 – 1.52 |
| Phase [AR] | 1.89 *** | 1.88 – 1.89 | 1.32 *** | 1.32 – 1.33 |
| Agency × Phase [AE] | 1.27 *** | 1.27 – 1.27 | 1.47 *** | 1.46 – 1.47 |
| Agency × Phase [BR] | 1.67 *** | 1.67 – 1.68 | 1.72 *** | 1.72 – 1.73 |
| Agency × Phase [AR] | 0.74 *** | 0.74 – 0.74 | 0.78 *** | 0.78 – 0.78 |
| Zero-Inflated Model | ||||
| (Intercept) | 0.06 *** | 0.05 – 0.07 | 0.08 *** | 0.07 – 0.09 |
| Agency | 0.38 *** | 0.30 – 0.47 | 0.52 *** | 0.43 – 0.63 |
| Phase [AE] | 0.89 | 0.75 – 1.06 | 1.25 ** | 1.08 – 1.44 |
| Phase [BR] | 0.66 *** | 0.55 – 0.79 | 1.10 | 0.95 – 1.26 |
| Phase [AR] | 0.52 *** | 0.43 – 0.64 | 0.92 | 0.79 – 1.07 |
| Agency × Phase [AE] | 0.89 | 0.64 – 1.24 | 0.64 ** | 0.49 – 0.84 |
| Agency × Phase [BR] | 1.00 | 0.72 – 1.40 | 0.73 * | 0.56 – 0.93 |
| Agency × Phase [AR] | 0.97 | 0.66 – 1.41 | 0.59 *** | 0.44 – 0.78 |
| Random Effects | ||||
| σ2 | 0.00 | 0.00 | ||
| τ00 | 4.01 Name | 3.22 Name | ||
| ICC | 1.00 | 1.00 | ||
| N | 847 Name | 847 Name | ||
| Observations | 60000 | 60000 | ||
| Marginal R2 / Conditional R2 | 0.044 / 1.000 | 0.024 / 1.000 | ||
| * p<0.05 ** p<0.01 *** p<0.001 | ||||
./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/x-summary-tab-model-i0001-base.html
Tabulate ALL glmmTMB Models
| Like Count | Retweet Count | Like Count | Like Count | |||||
|---|---|---|---|---|---|---|---|---|
| Predictors | Incidence Rate Ratios | CI | Incidence Rate Ratios | CI | Incidence Rate Ratios | CI | Incidence Rate Ratios | CI |
| (Intercept) | 54.85 *** | 47.88 – 62.83 | 21.17 *** | 18.73 – 23.94 | 30.07 *** | 24.65 – 36.69 | 30.07 *** | 24.65 – 36.69 |
| Agency | 0.84 *** | 0.84 – 0.85 | 0.75 *** | 0.74 – 0.75 | 0.79 *** | 0.79 – 0.79 | 0.79 *** | 0.79 – 0.79 |
| Phase [AE] | 1.90 *** | 1.90 – 1.90 | 1.09 *** | 1.09 – 1.09 | 1.75 *** | 1.74 – 1.75 | 1.75 *** | 1.74 – 1.75 |
| Phase [BR] | 2.42 *** | 2.41 – 2.42 | 1.52 *** | 1.51 – 1.52 | 1.25 *** | 1.25 – 1.25 | 1.25 *** | 1.25 – 1.25 |
| Phase [AR] | 1.89 *** | 1.88 – 1.89 | 1.32 *** | 1.32 – 1.33 | 1.61 *** | 1.61 – 1.62 | 1.61 *** | 1.61 – 1.62 |
| Agency × Phase [AE] | 1.27 *** | 1.27 – 1.27 | 1.47 *** | 1.46 – 1.47 | 1.86 *** | 1.85 – 1.87 | 1.86 *** | 1.85 – 1.87 |
| Agency × Phase [BR] | 1.67 *** | 1.67 – 1.68 | 1.72 *** | 1.72 – 1.73 | 1.71 *** | 1.71 – 1.72 | 1.71 *** | 1.71 – 1.72 |
| Agency × Phase [AR] | 0.74 *** | 0.74 – 0.74 | 0.78 *** | 0.78 – 0.78 | 1.40 *** | 1.39 – 1.41 | 1.40 *** | 1.39 – 1.41 |
| Outcome [winner] | 2.95 *** | 2.27 – 3.83 | 2.95 *** | 2.27 – 3.83 | ||||
| Agency × Outcome [winner] | 1.12 *** | 1.11 – 1.12 | 1.12 *** | 1.11 – 1.12 | ||||
| Phase [AE] × Outcome [winner] | 1.15 *** | 1.15 – 1.15 | 1.15 *** | 1.15 – 1.15 | ||||
| Phase [BR] × Outcome [winner] | 2.24 *** | 2.23 – 2.24 | 2.24 *** | 2.23 – 2.24 | ||||
| Phase [AR] × Outcome [winner] | 1.24 *** | 1.24 – 1.24 | 1.24 *** | 1.24 – 1.24 | ||||
| (Agency × Phase [AE]) × Outcome [winner] | 0.65 *** | 0.64 – 0.65 | 0.65 *** | 0.64 – 0.65 | ||||
| (Agency × Phase [BR]) × Outcome [winner] | 0.90 *** | 0.90 – 0.91 | 0.90 *** | 0.90 – 0.91 | ||||
| (Agency × Phase [AR]) × Outcome [winner] | 0.48 *** | 0.48 – 0.49 | 0.48 *** | 0.48 – 0.49 | ||||
| Zero-Inflated Model | ||||||||
| (Intercept) | 0.06 *** | 0.05 – 0.07 | 0.08 *** | 0.07 – 0.09 | 0.10 *** | 0.09 – 0.11 | 0.10 *** | 0.09 – 0.11 |
| Agency | 0.38 *** | 0.30 – 0.47 | 0.52 *** | 0.43 – 0.63 | 0.34 *** | 0.26 – 0.45 | 0.34 *** | 0.26 – 0.45 |
| Phase [AE] | 0.89 | 0.75 – 1.06 | 1.25 ** | 1.08 – 1.44 | 1.22 | 0.99 – 1.50 | 1.22 | 0.99 – 1.50 |
| Phase [BR] | 0.66 *** | 0.55 – 0.79 | 1.10 | 0.95 – 1.26 | 0.91 | 0.74 – 1.12 | 0.91 | 0.74 – 1.12 |
| Phase [AR] | 0.52 *** | 0.43 – 0.64 | 0.92 | 0.79 – 1.07 | 0.88 | 0.71 – 1.11 | 0.88 | 0.71 – 1.11 |
| Agency × Phase [AE] | 0.89 | 0.64 – 1.24 | 0.64 ** | 0.49 – 0.84 | 1.82 ** | 1.22 – 2.70 | 1.82 ** | 1.22 – 2.70 |
| Agency × Phase [BR] | 1.00 | 0.72 – 1.40 | 0.73 * | 0.56 – 0.93 | 1.90 ** | 1.28 – 2.80 | 1.90 ** | 1.28 – 2.80 |
| Agency × Phase [AR] | 0.97 | 0.66 – 1.41 | 0.59 *** | 0.44 – 0.78 | 1.78 * | 1.14 – 2.80 | 1.78 * | 1.14 – 2.80 |
| Outcome [winner] | 0.26 *** | 0.19 – 0.34 | 0.26 *** | 0.19 – 0.34 | ||||
| Agency × Outcome [winner] | 1.86 * | 1.12 – 3.11 | 1.86 * | 1.12 – 3.11 | ||||
| Phase [AE] × Outcome [winner] | 0.62 * | 0.41 – 0.93 | 0.62 * | 0.41 – 0.93 | ||||
| Phase [BR] × Outcome [winner] | 0.36 *** | 0.22 – 0.58 | 0.36 *** | 0.22 – 0.58 | ||||
| Phase [AR] × Outcome [winner] | 0.29 *** | 0.17 – 0.50 | 0.29 *** | 0.17 – 0.50 | ||||
| (Agency × Phase [AE]) × Outcome [winner] | 0.27 *** | 0.13 – 0.58 | 0.27 *** | 0.13 – 0.58 | ||||
| (Agency × Phase [BR]) × Outcome [winner] | 0.36 * | 0.15 – 0.84 | 0.36 * | 0.15 – 0.84 | ||||
| (Agency × Phase [AR]) × Outcome [winner] | 1.03 | 0.43 – 2.48 | 1.03 | 0.43 – 2.48 | ||||
| Random Effects | ||||||||
| σ2 | 0.00 | 0.00 | 0.00 | 0.00 | ||||
| τ00 | 4.01 Name | 3.22 Name | 3.63 Name | 3.63 Name | ||||
| ICC | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| N | 847 Name | 847 Name | 847 Name | 847 Name | ||||
| Observations | 60000 | 60000 | 60000 | 60000 | ||||
| Marginal R2 / Conditional R2 | 0.044 / 1.000 | 0.024 / 1.000 | 0.135 / 1.000 | 0.135 / 1.000 | ||||
| * p<0.05 ** p<0.01 *** p<0.001 | ||||||||
./data/20240428T200156-politicians-aux-analysis/n0001-init//n0001-models-phase-i0008-all/x-summary-tab-model-i0002-ALL.html
Report xFit05aPhLikes
We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency and Phase (formula: LikeCount ~
Agency * Phase). The model included Name as random effect (formula: ~1 | Name).
The model's total explanatory power is substantial (conditional R2 = 1.00) and
the part related to the fixed effects alone (marginal R2) is of 0.04. The
model's intercept, corresponding to Agency = 0 and Phase = BE, is at 4.00 (95%
CI [3.87, 4.14], p < .001). Within this model:
- The effect of Agency is statistically significant and negative (beta = -0.17,
95% CI [-0.17, -0.17], p < .001; Std. beta = -0.06, 95% CI [-0.06, -0.06])
- The effect of Phase [AE] is statistically significant and positive (beta =
0.64, 95% CI [0.64, 0.64], p < .001; Std. beta = 0.76, 95% CI [0.76, 0.76])
- The effect of Phase [BR] is statistically significant and positive (beta =
0.88, 95% CI [0.88, 0.88], p < .001; Std. beta = 1.14, 95% CI [1.13, 1.14])
- The effect of Phase [AR] is statistically significant and positive (beta =
0.63, 95% CI [0.63, 0.64], p < .001; Std. beta = 0.49, 95% CI [0.49, 0.49])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.24, 95% CI [0.24, 0.24], p < .001; Std. beta = 0.09, 95% CI [0.09,
0.09])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.51, 95% CI [0.51, 0.52], p < .001; Std. beta = 0.19, 95% CI [0.19,
0.19])
- The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.30, 95% CI [-0.30, -0.30], p < .001; Std. beta = -0.11, 95% CI
[-0.11, -0.11])
- The effect of Agency is statistically significant and negative (beta = -0.98,
95% CI [-1.21, -0.75], p < .001; Std. beta = -0.36, 95% CI [-0.45, -0.27])
- The effect of Phase [AE] is statistically non-significant and negative (beta
= -0.11, 95% CI [-0.29, 0.06], p = 0.205; Std. beta = -0.17, 95% CI [-0.30,
-0.04])
- The effect of Phase [BR] is statistically significant and negative (beta =
-0.41, 95% CI [-0.59, -0.23], p < .001; Std. beta = -0.41, 95% CI [-0.55,
-0.27])
- The effect of Phase [AR] is statistically significant and negative (beta =
-0.65, 95% CI [-0.85, -0.44], p < .001; Std. beta = -0.66, 95% CI [-0.81,
-0.51])
- The effect of Agency × Phase [AE] is statistically non-significant and
negative (beta = -0.12, 95% CI [-0.45, 0.22], p = 0.492; Std. beta = -0.04, 95%
CI [-0.17, 0.08])
- The effect of Agency × Phase [BR] is statistically non-significant and
positive (beta = 3.81e-03, 95% CI [-0.33, 0.33], p = 0.982; Std. beta =
9.86e-04, 95% CI [-0.12, 0.12])
- The effect of Agency × Phase [AR] is statistically non-significant and
negative (beta = -0.03, 95% CI [-0.41, 0.35], p = 0.871; Std. beta = -0.01, 95%
CI [-0.15, 0.13])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.
Report xFit06aPhRetweets
We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict RetweetCount with Agency and Phase (formula: RetweetCount
~ Agency * Phase). The model included Name as random effect (formula: ~1 |
Name). The model's total explanatory power is substantial (conditional R2 =
1.00) and the part related to the fixed effects alone (marginal R2) is of 0.02.
The model's intercept, corresponding to Agency = 0 and Phase = BE, is at 3.05
(95% CI [2.93, 3.18], p < .001). Within this model:
- The effect of Agency is statistically significant and negative (beta = -0.29,
95% CI [-0.29, -0.29], p < .001; Std. beta = -0.11, 95% CI [-0.11, -0.11])
- The effect of Phase [AE] is statistically significant and positive (beta =
0.09, 95% CI [0.08, 0.09], p < .001; Std. beta = 0.27, 95% CI [0.27, 0.28])
- The effect of Phase [BR] is statistically significant and positive (beta =
0.42, 95% CI [0.41, 0.42], p < .001; Std. beta = 0.68, 95% CI [0.68, 0.69])
- The effect of Phase [AR] is statistically significant and positive (beta =
0.28, 95% CI [0.28, 0.28], p < .001; Std. beta = 0.16, 95% CI [0.16, 0.16])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.38, 95% CI [0.38, 0.39], p < .001; Std. beta = 0.14, 95% CI [0.14,
0.14])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.54, 0.55], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
- The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.25, 95% CI [-0.25, -0.24], p < .001; Std. beta = -0.09, 95% CI
[-0.09, -0.09])
- The effect of Agency is statistically significant and negative (beta = -0.65,
95% CI [-0.84, -0.46], p < .001; Std. beta = -0.24, 95% CI [-0.31, -0.17])
- The effect of Phase [AE] is statistically significant and positive (beta =
0.22, 95% CI [0.08, 0.37], p = 0.002; Std. beta = 7.69e-03, 95% CI [-0.09,
0.11])
- The effect of Phase [BR] is statistically non-significant and positive (beta
= 0.09, 95% CI [-0.05, 0.23], p = 0.191; Std. beta = -0.06, 95% CI [-0.17,
0.04])
- The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.08, 95% CI [-0.23, 0.07], p = 0.290; Std. beta = -0.34, 95% CI [-0.45,
-0.23])
- The effect of Agency × Phase [AE] is statistically significant and negative
(beta = -0.44, 95% CI [-0.71, -0.18], p = 0.001; Std. beta = -0.16, 95% CI
[-0.26, -0.07])
- The effect of Agency × Phase [BR] is statistically significant and negative
(beta = -0.32, 95% CI [-0.57, -0.07], p = 0.013; Std. beta = -0.12, 95% CI
[-0.21, -0.02])
- The effect of Agency × Phase [AR] is statistically significant and negative
(beta = -0.53, 95% CI [-0.81, -0.25], p < .001; Std. beta = -0.20, 95% CI
[-0.30, -0.09])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.
Report xFit05xPhLikes
We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency, Phase and Outcome (formula:
LikeCount ~ Agency * Phase * Outcome). The model included Name as random effect
(formula: ~1 | Name). The model's total explanatory power is substantial
(conditional R2 = 1.00) and the part related to the fixed effects alone
(marginal R2) is of 0.14. The model's intercept, corresponding to Agency = 0,
Phase = BE and Outcome = loser, is at 3.40 (95% CI [3.20, 3.60], p < .001).
Within this model:
- The effect of Agency is statistically significant and negative (beta = -0.24,
95% CI [-0.24, -0.23], p < .001; Std. beta = -0.09, 95% CI [-0.09, -0.09])
- The effect of Phase [AE] is statistically significant and positive (beta =
0.56, 95% CI [0.56, 0.56], p < .001; Std. beta = 0.86, 95% CI [0.86, 0.86])
- The effect of Phase [BR] is statistically significant and positive (beta =
0.22, 95% CI [0.22, 0.22], p < .001; Std. beta = 0.49, 95% CI [0.48, 0.49])
- The effect of Phase [AR] is statistically significant and positive (beta =
0.48, 95% CI [0.48, 0.48], p < .001; Std. beta = 0.64, 95% CI [0.64, 0.64])
- The effect of Outcome [winner] is statistically significant and positive
(beta = 1.08, 95% CI [0.82, 1.34], p < .001; Std. beta = 1.09, 95% CI [0.83,
1.36])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.62, 95% CI [0.61, 0.62], p < .001; Std. beta = 0.23, 95% CI [0.23,
0.23])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.53, 0.54], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
- The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.34, 95% CI [0.33, 0.34], p < .001; Std. beta = 0.12, 95% CI [0.12,
0.13])
- The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.11, 95% CI [0.10, 0.11], p < .001; Std. beta = 0.04, 95% CI
[0.04, 0.04])
- The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.14, 95% CI [0.14, 0.14], p < .001; Std. beta = -0.08, 95% CI
[-0.08, -0.07])
- The effect of Phase [BR] × Outcome [winner] is statistically significant and
positive (beta = 0.80, 95% CI [0.80, 0.81], p < .001; Std. beta = 0.76, 95% CI
[0.75, 0.76])
- The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.21, 95% CI [0.21, 0.22], p < .001; Std. beta = -0.14, 95% CI
[-0.15, -0.14])
- The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -0.44, 95% CI [-0.44, -0.43], p < .001; Std.
beta = -0.16, 95% CI [-0.16, -0.16])
- The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -0.10, 95% CI [-0.11, -0.10], p < .001; Std.
beta = -0.04, 95% CI [-0.04, -0.04])
- The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.73, 95% CI [-0.73, -0.72], p < .001; Std.
beta = -0.27, 95% CI [-0.27, -0.27])
- The effect of Agency is statistically significant and negative (beta = -1.08,
95% CI [-1.36, -0.80], p < .001; Std. beta = -0.38, 95% CI [-0.48, -0.28])
- The effect of Phase [AE] is statistically non-significant and positive (beta
= 0.20, 95% CI [-9.68e-03, 0.40], p = 0.062; Std. beta = 0.46, 95% CI [0.29,
0.62])
- The effect of Phase [BR] is statistically non-significant and negative (beta
= -0.09, 95% CI [-0.30, 0.11], p = 0.369; Std. beta = 0.22, 95% CI [0.05,
0.38])
- The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.12, 95% CI [-0.35, 0.10], p = 0.290; Std. beta = 0.15, 95% CI [-0.04,
0.35])
- The effect of Outcome [winner] is statistically significant and negative
(beta = -1.37, 95% CI [-1.66, -1.08], p < .001; Std. beta = -1.07, 95% CI
[-1.25, -0.88])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.60, 95% CI [0.20, 0.99], p = 0.003; Std. beta = 0.21, 95% CI [0.06,
0.35])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.64, 95% CI [0.25, 1.03], p = 0.001; Std. beta = 0.24, 95% CI [0.10,
0.39])
- The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.58, 95% CI [0.13, 1.03], p = 0.012; Std. beta = 0.21, 95% CI [0.04,
0.37])
- The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.62, 95% CI [0.11, 1.13], p = 0.017; Std. beta = 0.24, 95% CI
[0.06, 0.43])
- The effect of Phase [AE] × Outcome [winner] is statistically significant and
negative (beta = -0.48, 95% CI [-0.89, -0.07], p = 0.021; Std. beta = -1.04,
95% CI [-1.33, -0.76])
- The effect of Phase [BR] × Outcome [winner] is statistically significant and
negative (beta = -1.03, 95% CI [-1.51, -0.55], p < .001; Std. beta = -1.41, 95%
CI [-1.74, -1.08])
- The effect of Phase [AR] × Outcome [winner] is statistically significant and
negative (beta = -1.22, 95% CI [-1.75, -0.70], p < .001; Std. beta = -1.14, 95%
CI [-1.46, -0.82])
- The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -1.30, 95% CI [-2.06, -0.55], p < .001; Std.
beta = -0.43, 95% CI [-0.71, -0.16])
- The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -1.03, 95% CI [-1.87, -0.18], p = 0.018; Std.
beta = -0.35, 95% CI [-0.65, -0.05])
- The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
non-significant and positive (beta = 0.03, 95% CI [-0.84, 0.91], p = 0.941;
Std. beta = -0.02, 95% CI [-0.34, 0.29])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.
Report xFit06xPhRetweets
We fitted a zero-inflated poisson mixed model (estimated using ML and nlminb
optimizer) to predict LikeCount with Agency, Phase and Outcome (formula:
LikeCount ~ Agency * Phase * Outcome). The model included Name as random effect
(formula: ~1 | Name). The model's total explanatory power is substantial
(conditional R2 = 1.00) and the part related to the fixed effects alone
(marginal R2) is of 0.14. The model's intercept, corresponding to Agency = 0,
Phase = BE and Outcome = loser, is at 3.40 (95% CI [3.20, 3.60], p < .001).
Within this model:
- The effect of Agency is statistically significant and negative (beta = -0.24,
95% CI [-0.24, -0.23], p < .001; Std. beta = -0.09, 95% CI [-0.09, -0.09])
- The effect of Phase [AE] is statistically significant and positive (beta =
0.56, 95% CI [0.56, 0.56], p < .001; Std. beta = 0.86, 95% CI [0.86, 0.86])
- The effect of Phase [BR] is statistically significant and positive (beta =
0.22, 95% CI [0.22, 0.22], p < .001; Std. beta = 0.49, 95% CI [0.48, 0.49])
- The effect of Phase [AR] is statistically significant and positive (beta =
0.48, 95% CI [0.48, 0.48], p < .001; Std. beta = 0.64, 95% CI [0.64, 0.64])
- The effect of Outcome [winner] is statistically significant and positive
(beta = 1.08, 95% CI [0.82, 1.34], p < .001; Std. beta = 1.09, 95% CI [0.83,
1.36])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.62, 95% CI [0.61, 0.62], p < .001; Std. beta = 0.23, 95% CI [0.23,
0.23])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.54, 95% CI [0.53, 0.54], p < .001; Std. beta = 0.20, 95% CI [0.20,
0.20])
- The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.34, 95% CI [0.33, 0.34], p < .001; Std. beta = 0.12, 95% CI [0.12,
0.13])
- The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.11, 95% CI [0.10, 0.11], p < .001; Std. beta = 0.04, 95% CI
[0.04, 0.04])
- The effect of Phase [AE] × Outcome [winner] is statistically significant and
positive (beta = 0.14, 95% CI [0.14, 0.14], p < .001; Std. beta = -0.08, 95% CI
[-0.08, -0.07])
- The effect of Phase [BR] × Outcome [winner] is statistically significant and
positive (beta = 0.80, 95% CI [0.80, 0.81], p < .001; Std. beta = 0.76, 95% CI
[0.75, 0.76])
- The effect of Phase [AR] × Outcome [winner] is statistically significant and
positive (beta = 0.21, 95% CI [0.21, 0.22], p < .001; Std. beta = -0.14, 95% CI
[-0.15, -0.14])
- The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -0.44, 95% CI [-0.44, -0.43], p < .001; Std.
beta = -0.16, 95% CI [-0.16, -0.16])
- The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -0.10, 95% CI [-0.11, -0.10], p < .001; Std.
beta = -0.04, 95% CI [-0.04, -0.04])
- The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
significant and negative (beta = -0.73, 95% CI [-0.73, -0.72], p < .001; Std.
beta = -0.27, 95% CI [-0.27, -0.27])
- The effect of Agency is statistically significant and negative (beta = -1.08,
95% CI [-1.36, -0.80], p < .001; Std. beta = -0.38, 95% CI [-0.48, -0.28])
- The effect of Phase [AE] is statistically non-significant and positive (beta
= 0.20, 95% CI [-9.68e-03, 0.40], p = 0.062; Std. beta = 0.46, 95% CI [0.29,
0.62])
- The effect of Phase [BR] is statistically non-significant and negative (beta
= -0.09, 95% CI [-0.30, 0.11], p = 0.369; Std. beta = 0.22, 95% CI [0.05,
0.38])
- The effect of Phase [AR] is statistically non-significant and negative (beta
= -0.12, 95% CI [-0.35, 0.10], p = 0.290; Std. beta = 0.15, 95% CI [-0.04,
0.35])
- The effect of Outcome [winner] is statistically significant and negative
(beta = -1.37, 95% CI [-1.66, -1.08], p < .001; Std. beta = -1.07, 95% CI
[-1.25, -0.88])
- The effect of Agency × Phase [AE] is statistically significant and positive
(beta = 0.60, 95% CI [0.20, 0.99], p = 0.003; Std. beta = 0.21, 95% CI [0.06,
0.35])
- The effect of Agency × Phase [BR] is statistically significant and positive
(beta = 0.64, 95% CI [0.25, 1.03], p = 0.001; Std. beta = 0.24, 95% CI [0.10,
0.39])
- The effect of Agency × Phase [AR] is statistically significant and positive
(beta = 0.58, 95% CI [0.13, 1.03], p = 0.012; Std. beta = 0.21, 95% CI [0.04,
0.37])
- The effect of Agency × Outcome [winner] is statistically significant and
positive (beta = 0.62, 95% CI [0.11, 1.13], p = 0.017; Std. beta = 0.24, 95% CI
[0.06, 0.43])
- The effect of Phase [AE] × Outcome [winner] is statistically significant and
negative (beta = -0.48, 95% CI [-0.89, -0.07], p = 0.021; Std. beta = -1.04,
95% CI [-1.33, -0.76])
- The effect of Phase [BR] × Outcome [winner] is statistically significant and
negative (beta = -1.03, 95% CI [-1.51, -0.55], p < .001; Std. beta = -1.41, 95%
CI [-1.74, -1.08])
- The effect of Phase [AR] × Outcome [winner] is statistically significant and
negative (beta = -1.22, 95% CI [-1.75, -0.70], p < .001; Std. beta = -1.14, 95%
CI [-1.46, -0.82])
- The effect of (Agency × Phase [AE]) × Outcome [winner] is statistically
significant and negative (beta = -1.30, 95% CI [-2.06, -0.55], p < .001; Std.
beta = -0.43, 95% CI [-0.71, -0.16])
- The effect of (Agency × Phase [BR]) × Outcome [winner] is statistically
significant and negative (beta = -1.03, 95% CI [-1.87, -0.18], p = 0.018; Std.
beta = -0.35, 95% CI [-0.65, -0.05])
- The effect of (Agency × Phase [AR]) × Outcome [winner] is statistically
non-significant and positive (beta = 0.03, 95% CI [-0.84, 0.91], p = 0.941;
Std. beta = -0.02, 95% CI [-0.34, 0.29])
Standardized parameters were obtained by fitting the model on a standardized
version of the dataset. 95% Confidence Intervals (CIs) and p-values were
computed using a Wald z-distribution approximation.
Save Workspace
Model xFit21aPhOutcome
Fit
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
Family: binomial ( logit )
Formula: Outcome ~ Agency + (1 | Name)
Data: df6
AIC BIC logLik deviance df.resid
1346.4 1378.2 -670.2 1340.4 304617
Random effects:
Conditional model:
Groups Name Variance Std.Dev.
Name (Intercept) 13586 116.6
Number of obs: 304620, groups: Name, 850
Conditional model:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 18.8140 0.7048 26.693 <2e-16 ***
Agency 0.1325 0.8099 0.164 0.87
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
---------------------------------------------------------------------
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# R2 for Mixed Models
Conditional R2: 1.000
Marginal R2: 0.000
---------------------------------------------------------------------
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# Intraclass Correlation Coefficient
Adjusted ICC: 1.000
Unadjusted ICC: 1.000
---------------------------------------------------------------------
xFit21aPhOutcome: [df6] Outcome ~ Agency + (1 | Name)
# ICC by Group
Group | ICC
-------------
Name | 1.000
---------------------------------------------------------------------
Save Workspace
List important variables
=====================================================================
df0
df2
df3
df5
df6
df8
=====================================================================
fit01aPh
fit02aPh
fit03aPh
fit04aPh
fit04xPh
xFit05aPhLikes
xFit05xPhLikes
xFit06aPhRetweets
xFit06xPhRetweets
xFit21aPhOutcome